Compare commits

..

171 Commits

Author SHA1 Message Date
joachim-danswer
a4b780e27f streaming + saving of search docs of no verified ones available
- sub-questions only
2025-01-19 21:25:27 -08:00
joachim-danswer
dffda7d0c0 added logging to log_messages 2025-01-19 19:28:20 -08:00
joachim-danswer
79f7ca29d1 merge with Evan changes & ProSearchConfig -> AgentSearchConfig 2025-01-19 15:19:55 -08:00
joachim-danswer
2a8898527b new directory structure
- also nodes got moved to individual files
2025-01-19 14:51:26 -08:00
Evan Lohn
0de3a6fe6b stream finished events 2025-01-19 13:18:30 -08:00
joachim-danswer
a35ef19f71 Stream pre-verify results if no verified docs 2025-01-19 09:07:53 -08:00
Evan Lohn
e955279186 fixed pro search config creation 2025-01-18 17:42:07 -08:00
joachim-danswer
a48611ef57 Updated initial search flags for UI flows
- may need tweaking
2025-01-18 16:49:44 -08:00
Evan Lohn
6fe4ce1dd6 fix non updated key issue 2025-01-18 16:15:19 -08:00
Evan Lohn
640f64d5de fixed pro search flag and unnecessary/incorrect streaming 2025-01-18 15:59:29 -08:00
Evan Lohn
a0517a8da7 finish pro->agentic rename 2025-01-18 15:10:55 -08:00
joachim-danswer
afeb7f2dd8 prompt update to suggest doc citations vs question citations 2025-01-18 15:10:13 -08:00
joachim-danswer
91ee90b00d added 'Agent Search' decision 2025-01-18 14:39:00 -08:00
joachim-danswer
5d5a8b2218 Changed "I don't know" to a more appropriate response
And some other small prompt modifications.
2025-01-18 10:38:58 -08:00
joachim-danswer
7ef928794d optional search to inform decomposition
New Agent Search parameter:
  - perform_initial_search (default: False)
2025-01-18 10:16:00 -08:00
Evan Lohn
0df0b7147a name cleanup and WIP unifying input types 2025-01-17 19:54:15 -08:00
Evan Lohn
fb3bc2f259 working version with cleanup 2025-01-17 17:16:41 -08:00
Evan Lohn
e8fd57a1ac WIP 2025-01-17 17:06:43 -08:00
Evan Lohn
9d7c337ee6 skip answer verification for idk answers 2025-01-16 17:04:31 -08:00
Evan Lohn
38fd061ed5 cleanup hardcoded idks 2025-01-16 16:41:00 -08:00
Evan Lohn
7282447186 clean run_graph 2025-01-16 16:15:59 -08:00
joachim-danswer
b6da896240 removal of citations from previous answers 2025-01-16 14:26:41 -08:00
joachim-danswer
4dad841bfc new refined prompt 2025-01-16 14:25:44 -08:00
joachim-danswer
755b7579b5 sub_question number handling 2025-01-16 14:25:38 -08:00
Evan Lohn
42257244d9 finished checks for llm context window before invoking or streaming 2025-01-16 14:10:05 -08:00
joachim-danswer
3991eac4c0 new citation format 2025-01-15 17:17:04 -08:00
Evan Lohn
fabc9f7e4b attempted fix for early exit from langgraph event loop 2025-01-15 17:05:47 -08:00
Evan Lohn
7987a3a75e mypy error on unbound locals 2025-01-15 15:43:55 -08:00
Evan Lohn
ff24f82d52 unbound local error 2025-01-15 15:32:24 -08:00
Evan Lohn
563513698b fixed no good subquestions error 2025-01-15 15:23:59 -08:00
Evan Lohn
b2208195ce fixed streaming and persistence of answer docs 2025-01-15 14:55:52 -08:00
Evan Lohn
ac9ce7ca68 added back saved docs for agentic search 2025-01-15 14:23:24 -08:00
joachim-danswer
c9b34ed583 Updated citation handling on backend + citations for refined answer 2025-01-15 14:16:04 -08:00
Evan Lohn
2bc948fa73 dispatch initial question as dummy subquestion 2025-01-15 11:51:13 -08:00
Evan Lohn
8ea987e068 remove empty expanded subquestions 2025-01-15 11:35:00 -08:00
Evan Lohn
43e488275f context length fix 2025-01-15 11:35:00 -08:00
joachim-danswer
09d0820882 Question numbering fix (logging temp to info) 2025-01-15 11:30:46 -08:00
Evan Lohn
2c0ef2ea47 better separated dispatch 2025-01-15 10:26:38 -08:00
Evan Lohn
7cca660a93 handle prompts that exceed context window 2025-01-14 18:58:12 -08:00
Evan Lohn
ab70b7c303 persistence of refined agent answer and top-level handling of fine grained citations (WIP) 2025-01-14 17:28:40 -08:00
pablodanswer
0ff212a2b4 alembic migration 2025-01-14 14:41:14 -08:00
pablodanswer
5c31171b37 Merge branch 'pro-search' of github.com:onyx-dot-app/onyx into pro-search 2025-01-14 14:38:27 -08:00
pablodanswer
1669a5d69f alembic migration 2025-01-14 14:37:59 -08:00
pablodanswer
60db37fac1 alembic migration 2025-01-14 14:35:43 -08:00
joachim-danswer
48a4e2c76b refined prompt fix 2025-01-14 14:35:43 -08:00
Evan Lohn
e1175e15da stream refined answer 2025-01-14 14:35:43 -08:00
Evan Lohn
27b044c030 fix local variable access issue 2025-01-14 14:35:43 -08:00
Evan Lohn
4a7c6a6561 subquestion numbers start at 1 2025-01-14 14:35:43 -08:00
Evan Lohn
78df113c7f un-break refinement flow and stream answer 2025-01-14 14:35:43 -08:00
Evan Lohn
113767a061 stream stop info consistency 2025-01-14 14:35:43 -08:00
pablodanswer
1851c836dc alembic migration 2025-01-14 14:35:43 -08:00
Evan Lohn
413a4e55f5 use correct doc id 2025-01-14 14:35:43 -08:00
Evan Lohn
dfcf8791e7 tool call kickoffs for starting agentic, starting refined 2025-01-14 14:35:43 -08:00
Evan Lohn
1b9f128851 verified docs for persisted info 2025-01-14 14:35:43 -08:00
Evan Lohn
d38b9bd194 cleanup run_graph and added stream stopping for sub_answers 2025-01-14 14:35:43 -08:00
Evan Lohn
ee304c9c35 improved no-subquestion-gen handling 2025-01-14 14:35:43 -08:00
joachim-danswer
4c75b73fa8 Pro_search B + fix for no docs retrieved 2025-01-14 14:35:43 -08:00
Evan Lohn
70509fbe7e attach persisted agent search info to assistant message 2025-01-14 14:35:43 -08:00
Evan Lohn
6bea880695 added subquestion info to streamed docs, removed extra deduping 2025-01-14 14:35:43 -08:00
Evan Lohn
249dd96f25 tentative fix for not persisting search docs 2025-01-14 14:35:43 -08:00
Evan Lohn
f0e74618e2 fixed issue when tool call unnecessary 2025-01-14 14:35:43 -08:00
Evan Lohn
3e27b79040 better answer persistence 2025-01-14 14:35:43 -08:00
Evan Lohn
91a37ef345 save agent answers 2025-01-14 14:35:43 -08:00
Evan Lohn
6c2f4e4775 fix citation processing in basic search 2025-01-14 14:35:43 -08:00
Evan Lohn
87101c8c74 fix run_graph testing script 2025-01-14 14:35:43 -08:00
Evan Lohn
9887be3dfc fixed issues with standard flow 2025-01-14 14:35:43 -08:00
Evan Lohn
22e209afc8 add back old citation processing temporarily 2025-01-14 14:35:43 -08:00
Evan Lohn
05a4792575 fix heads issue 2025-01-14 14:35:43 -08:00
Evan Lohn
f79d44bd6e Pro search clean commmit. See evan_answer_rework branch for prior history 2025-01-14 14:35:43 -08:00
pablonyx
5081d240ce Proper anonymous user restricting (#3645) 2025-01-14 14:35:42 -08:00
pablodanswer
a570d39301 validated 2025-01-14 14:15:41 -08:00
pablodanswer
cd9279f0e1 additional label filtering 2025-01-14 13:49:12 -08:00
pablodanswer
72d1928b8f label editing / deletion 2025-01-14 13:45:49 -08:00
pablodanswer
086bba6454 fully cleaned assistant editor 2025-01-14 13:40:41 -08:00
pablodanswer
289be0a423 user settings etc. 2025-01-14 13:31:37 -08:00
pablodanswer
862a62483c various improvements 2025-01-14 13:19:25 -08:00
pablodanswer
694925d81d k 2025-01-14 12:33:34 -08:00
pablodanswer
478eb511fa add shortcuts, reorganize various pages,update seeding, starter messages, etc. 2025-01-14 12:30:05 -08:00
pablodanswer
a259f92f39 alembic migration 2025-01-13 20:55:52 -08:00
joachim-danswer
9592f0a494 refined prompt fix 2025-01-13 20:54:39 -08:00
Evan Lohn
07c2336c08 stream refined answer 2025-01-13 20:54:39 -08:00
Evan Lohn
7350dd73d1 fix local variable access issue 2025-01-13 20:54:39 -08:00
Evan Lohn
8f428cfcec subquestion numbers start at 1 2025-01-13 20:54:39 -08:00
Evan Lohn
3610a51222 un-break refinement flow and stream answer 2025-01-13 20:54:39 -08:00
Evan Lohn
e0654c2209 stream stop info consistency 2025-01-13 20:54:39 -08:00
pablodanswer
99d7c09433 alembic migration 2025-01-13 20:54:39 -08:00
Evan Lohn
6803702ca3 use correct doc id 2025-01-13 20:54:39 -08:00
Evan Lohn
4ea0ca5a78 tool call kickoffs for starting agentic, starting refined 2025-01-13 20:54:39 -08:00
Evan Lohn
561e44e443 verified docs for persisted info 2025-01-13 20:54:39 -08:00
Evan Lohn
931a119498 cleanup run_graph and added stream stopping for sub_answers 2025-01-13 20:54:39 -08:00
Evan Lohn
fddc1882d1 improved no-subquestion-gen handling 2025-01-13 20:54:39 -08:00
joachim-danswer
086d70a085 Pro_search B + fix for no docs retrieved 2025-01-13 20:54:39 -08:00
Evan Lohn
5a832628e2 attach persisted agent search info to assistant message 2025-01-13 20:54:39 -08:00
Evan Lohn
dfe1ed4c66 added subquestion info to streamed docs, removed extra deduping 2025-01-13 20:54:39 -08:00
Evan Lohn
5761557c19 tentative fix for not persisting search docs 2025-01-13 20:54:39 -08:00
Evan Lohn
29c479f496 fixed issue when tool call unnecessary 2025-01-13 20:54:39 -08:00
Evan Lohn
b60002c791 better answer persistence 2025-01-13 20:54:39 -08:00
Evan Lohn
b49c5afb09 save agent answers 2025-01-13 20:54:39 -08:00
Evan Lohn
b15e29619a fix citation processing in basic search 2025-01-13 20:54:39 -08:00
Evan Lohn
119336035e fix run_graph testing script 2025-01-13 20:54:39 -08:00
Evan Lohn
25bb5983af fixed issues with standard flow 2025-01-13 20:54:39 -08:00
Evan Lohn
ca1c12f122 add back old citation processing temporarily 2025-01-13 20:54:39 -08:00
Evan Lohn
9b55643e55 fix heads issue 2025-01-13 20:54:39 -08:00
Evan Lohn
233bbfa4e4 Pro search clean commmit. See evan_answer_rework branch for prior history 2025-01-13 20:54:36 -08:00
pablonyx
8c67288197 Proper anonymous user restricting (#3645) 2025-01-13 20:54:05 -08:00
pablodanswer
26c5c57ddb quick v1 labels 2025-01-13 19:45:00 -08:00
pablodanswer
ac15d0002a k 2025-01-13 18:01:19 -08:00
pablodanswer
8cca29eeab fix width + editors 2025-01-13 17:58:25 -08:00
pablodanswer
a365ab0c7d remove some whitespace 2025-01-13 17:55:29 -08:00
pablodanswer
fd89d1e141 quick nit 2025-01-13 17:53:38 -08:00
pablodanswer
7e32d21236 push quick changes from diff 2025-01-13 17:52:08 -08:00
pablodanswer
71eab9c740 push 2025-01-13 17:47:36 -08:00
pablodanswer
5c4451c084 :wMerge branch 'new_ux_branch' of github.com:onyx-dot-app/onyx into new_ux_branch 2025-01-13 17:34:37 -08:00
pablodanswer
2c894aaf07 quick nit 2025-01-13 17:32:04 -08:00
Yuhong Sun
bf3da9f9cf k 2025-01-13 17:25:31 -08:00
Yuhong Sun
4506770dd9 Yuhong 2025-01-13 17:16:15 -08:00
pablodanswer
25e2dfa5df k 2025-01-13 13:45:20 -08:00
pablodanswer
ba2d5fcc7d add input prompts 2025-01-13 13:43:41 -08:00
pablodanswer
f9be71ff24 l 2025-01-13 12:44:21 -08:00
pablodanswer
b92485223b sidebar 2025-01-13 12:44:04 -08:00
pablodanswer
5790f37648 quick nit 2025-01-13 12:41:32 -08:00
pablodanswer
b641cfc3e4 Merge branch 'new_ux_branch' of github.com:onyx-dot-app/onyx into new_ux_branch 2025-01-13 12:39:36 -08:00
pablodanswer
a2dfbb5b9c update assistant editor 2025-01-13 12:39:16 -08:00
Yuhong Sun
570ba9f0b6 Yuhong 2025-01-13 12:17:21 -08:00
pablodanswer
650fee6e2c quick updates 2025-01-13 12:00:47 -08:00
pablodanswer
8aa7fb5027 Merge branch 'new_ux_branch' of github.com:onyx-dot-app/onyx into new_ux_branch 2025-01-13 10:04:39 -08:00
pablodanswer
e4bf04fd94 update chat banner 2025-01-13 10:04:31 -08:00
Yuhong Sun
70de4708d0 Yuhong 2025-01-13 10:03:57 -08:00
pablodanswer
4ed9f0ffc7 editor changes 2025-01-12 21:22:35 -08:00
pablodanswer
7b67546199 k 2025-01-12 19:17:38 -08:00
pablodanswer
6c68a53c62 nit 2025-01-12 19:14:19 -08:00
pablodanswer
9e3b1d29aa nit 2025-01-12 18:25:40 -08:00
pablodanswer
ec7a606f4c popover within a popover > modal within a modal 2025-01-12 18:08:00 -08:00
pablodanswer
4e5bc7a4ba quick nit 2025-01-12 17:46:52 -08:00
pablodanswer
55d3b0f271 Merge branch 'new_ux_branch' of github.com:onyx-dot-app/onyx into new_ux_branch 2025-01-12 17:45:18 -08:00
pablodanswer
565bfa4e88 address all but modal within modal 2025-01-12 17:42:34 -08:00
Yuhong Sun
9ad10d1f60 Yuhong 2025-01-12 17:10:38 -08:00
pablodanswer
ad19e9aee7 k 2025-01-12 16:47:57 -08:00
pablodanswer
b11641c2bc most new fixes 2025-01-12 16:32:52 -08:00
pablodanswer
b7307813d5 quick nits 2025-01-12 16:22:21 -08:00
Yuhong Sun
3e8e544086 Yuhong 2025-01-12 14:03:36 -08:00
pablodanswer
7ba00f8b48 quick nit 2025-01-12 12:17:56 -08:00
pablodanswer
19204b49a7 final updates 2025-01-12 12:13:05 -08:00
pablodanswer
7254cb642d fully updated - groups 2025-01-12 12:01:39 -08:00
pablodanswer
da27c8be6d k 2025-01-11 20:28:12 -08:00
pablodanswer
9d0272fe62 minor nit 2025-01-11 19:13:45 -08:00
pablodanswer
167b5bad49 additioanl nits 2025-01-11 17:14:01 -08:00
pablodanswer
3acf235c84 quick nit 2025-01-11 17:07:53 -08:00
pablodanswer
0d9441da88 draggables 2025-01-11 17:02:59 -08:00
pablodanswer
a915e4dfa7 k 2025-01-11 11:45:50 -08:00
pablodanswer
7f2610e7d4 looking good 2025-01-11 11:24:09 -08:00
pablodanswer
19323472e6 nit 2025-01-10 19:24:33 -08:00
pablodanswer
be84cf95bf fix the hydra 2025-01-10 14:15:17 -08:00
pablodanswer
79d847f660 nit 2025-01-10 13:08:50 -08:00
pablodanswer
b06f56102e quick nit 2025-01-10 12:55:25 -08:00
pablodanswer
078ae4b9c7 add new ux 2025-01-10 12:54:00 -08:00
pablodanswer
5d034e08fc nit 2025-01-10 12:07:27 -08:00
pablodanswer
cafa0aac0d push minor changes 2025-01-10 12:07:27 -08:00
pablodanswer
f61864c36e nit 2025-01-10 12:07:27 -08:00
pablodanswer
5b0a1ccc31 minor nit 2025-01-10 12:07:27 -08:00
pablodanswer
acb9cca1e8 quick nits 2025-01-10 12:07:27 -08:00
pablodanswer
e22918e31d v3 2025-01-10 12:07:27 -08:00
pablodanswer
e5c430178d quick nits 2025-01-10 12:07:27 -08:00
pablodanswer
35f379b093 validate 2025-01-10 12:07:27 -08:00
pablodanswer
c85900e4f8 nit 2025-01-10 12:07:27 -08:00
pablodanswer
bf6b6342a1 quick addition 2025-01-10 12:07:27 -08:00
pablodanswer
9adbfc1b81 organize components 2025-01-10 12:07:27 -08:00
pablodanswer
b5dd5df36f quick nit 2025-01-10 12:07:27 -08:00
pablodanswer
6b0a2e11b5 k 2025-01-10 12:07:27 -08:00
pablodanswer
169f3fd0dc v2 2025-01-10 12:07:27 -08:00
pablodanswer
c15a828576 add chrome extension
minor clean up

additional handling

post rebase fixes

nit

quick bump

finalize

minor cleanup

organizational

Revert changes in backend directory

Revert changes in deployment directory

push misc changes

improve shortcut display + general nrf page layout

minor clean up

quick nit

update chrome

k

build fix

k

update

k
2025-01-10 12:07:26 -08:00
977 changed files with 24523 additions and 55150 deletions

View File

@@ -1,14 +1,11 @@
## Description
[Provide a brief description of the changes in this PR]
## How Has This Been Tested?
## How Has This Been Tested?
[Describe the tests you ran to verify your changes]
## Backporting (check the box to trigger backport action)
Note: You have to check that the action passes, otherwise resolve the conflicts manually and tag the patches.
- [ ] This PR should be backported (make sure to check that the backport attempt succeeds)
- [ ] [Optional] Override Linear Check

View File

@@ -65,11 +65,8 @@ jobs:
NEXT_PUBLIC_POSTHOG_KEY=${{ secrets.POSTHOG_KEY }}
NEXT_PUBLIC_POSTHOG_HOST=${{ secrets.POSTHOG_HOST }}
NEXT_PUBLIC_SENTRY_DSN=${{ secrets.SENTRY_DSN }}
NEXT_PUBLIC_STRIPE_PUBLISHABLE_KEY=${{ secrets.STRIPE_PUBLISHABLE_KEY }}
NEXT_PUBLIC_GTM_ENABLED=true
NEXT_PUBLIC_FORGOT_PASSWORD_ENABLED=true
NEXT_PUBLIC_INCLUDE_ERROR_POPUP_SUPPORT_LINK=true
NODE_OPTIONS=--max-old-space-size=8192
# needed due to weird interactions with the builds for different platforms
no-cache: true
labels: ${{ steps.meta.outputs.labels }}

View File

@@ -12,32 +12,7 @@ env:
BUILDKIT_PROGRESS: plain
jobs:
# 1) Preliminary job to check if the changed files are relevant
check_model_server_changes:
runs-on: ubuntu-latest
outputs:
changed: ${{ steps.check.outputs.changed }}
steps:
- name: Checkout code
uses: actions/checkout@v4
- name: Check if relevant files changed
id: check
run: |
# Default to "false"
echo "changed=false" >> $GITHUB_OUTPUT
# Compare the previous commit (github.event.before) to the current one (github.sha)
# If any file in backend/model_server/** or backend/Dockerfile.model_server is changed,
# set changed=true
if git diff --name-only ${{ github.event.before }} ${{ github.sha }} \
| grep -E '^backend/model_server/|^backend/Dockerfile.model_server'; then
echo "changed=true" >> $GITHUB_OUTPUT
fi
build-amd64:
needs: [check_model_server_changes]
if: needs.check_model_server_changes.outputs.changed == 'true'
runs-on:
[runs-on, runner=8cpu-linux-x64, "run-id=${{ github.run_id }}-amd64"]
steps:
@@ -77,8 +52,6 @@ jobs:
provenance: false
build-arm64:
needs: [check_model_server_changes]
if: needs.check_model_server_changes.outputs.changed == 'true'
runs-on:
[runs-on, runner=8cpu-linux-x64, "run-id=${{ github.run_id }}-arm64"]
steps:
@@ -118,8 +91,7 @@ jobs:
provenance: false
merge-and-scan:
needs: [build-amd64, build-arm64, check_model_server_changes]
if: needs.check_model_server_changes.outputs.changed == 'true'
needs: [build-amd64, build-arm64]
runs-on: ubuntu-latest
steps:
- name: Login to Docker Hub

View File

@@ -60,8 +60,6 @@ jobs:
push: true
build-args: |
ONYX_VERSION=${{ github.ref_name }}
NODE_OPTIONS=--max-old-space-size=8192
# needed due to weird interactions with the builds for different platforms
no-cache: true
labels: ${{ steps.meta.outputs.labels }}

View File

@@ -53,90 +53,24 @@ jobs:
exclude: '(?i)^(pylint|aio[-_]*).*'
- name: Print report
if: always()
if: ${{ always() }}
run: echo "${{ steps.license_check_report.outputs.report }}"
- name: Install npm dependencies
working-directory: ./web
run: npm ci
- name: Run Trivy vulnerability scanner in repo mode
uses: aquasecurity/trivy-action@0.28.0
with:
scan-type: fs
scanners: license
format: table
# format: sarif
# output: trivy-results.sarif
severity: HIGH,CRITICAL
# be careful enabling the sarif and upload as it may spam the security tab
# with a huge amount of items. Work out the issues before enabling upload.
# - name: Run Trivy vulnerability scanner in repo mode
# if: always()
# uses: aquasecurity/trivy-action@0.29.0
# - name: Upload Trivy scan results to GitHub Security tab
# uses: github/codeql-action/upload-sarif@v3
# with:
# scan-type: fs
# scan-ref: .
# scanners: license
# format: table
# severity: HIGH,CRITICAL
# # format: sarif
# # output: trivy-results.sarif
#
# # - name: Upload Trivy scan results to GitHub Security tab
# # uses: github/codeql-action/upload-sarif@v3
# # with:
# # sarif_file: trivy-results.sarif
scan-trivy:
# See https://runs-on.com/runners/linux/
runs-on: [runs-on,runner=2cpu-linux-x64,"run-id=${{ github.run_id }}"]
steps:
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
- name: Login to Docker Hub
uses: docker/login-action@v3
with:
username: ${{ secrets.DOCKER_USERNAME }}
password: ${{ secrets.DOCKER_TOKEN }}
# Backend
- name: Pull backend docker image
run: docker pull onyxdotapp/onyx-backend:latest
- name: Run Trivy vulnerability scanner on backend
uses: aquasecurity/trivy-action@0.29.0
env:
TRIVY_DB_REPOSITORY: 'public.ecr.aws/aquasecurity/trivy-db:2'
TRIVY_JAVA_DB_REPOSITORY: 'public.ecr.aws/aquasecurity/trivy-java-db:1'
with:
image-ref: onyxdotapp/onyx-backend:latest
scanners: license
severity: HIGH,CRITICAL
vuln-type: library
exit-code: 0 # Set to 1 if we want a failed scan to fail the workflow
# Web server
- name: Pull web server docker image
run: docker pull onyxdotapp/onyx-web-server:latest
- name: Run Trivy vulnerability scanner on web server
uses: aquasecurity/trivy-action@0.29.0
env:
TRIVY_DB_REPOSITORY: 'public.ecr.aws/aquasecurity/trivy-db:2'
TRIVY_JAVA_DB_REPOSITORY: 'public.ecr.aws/aquasecurity/trivy-java-db:1'
with:
image-ref: onyxdotapp/onyx-web-server:latest
scanners: license
severity: HIGH,CRITICAL
vuln-type: library
exit-code: 0
# Model server
- name: Pull model server docker image
run: docker pull onyxdotapp/onyx-model-server:latest
- name: Run Trivy vulnerability scanner
uses: aquasecurity/trivy-action@0.29.0
env:
TRIVY_DB_REPOSITORY: 'public.ecr.aws/aquasecurity/trivy-db:2'
TRIVY_JAVA_DB_REPOSITORY: 'public.ecr.aws/aquasecurity/trivy-java-db:1'
with:
image-ref: onyxdotapp/onyx-model-server:latest
scanners: license
severity: HIGH,CRITICAL
vuln-type: library
exit-code: 0
# sarif_file: trivy-results.sarif

View File

@@ -1,6 +1,6 @@
name: Run Playwright Tests
name: Run Chromatic Tests
concurrency:
group: Run-Playwright-Tests-${{ github.workflow }}-${{ github.head_ref || github.event.workflow_run.head_branch || github.run_id }}
group: Run-Chromatic-Tests-${{ github.workflow }}-${{ github.head_ref || github.event.workflow_run.head_branch || github.run_id }}
cancel-in-progress: true
on: push
@@ -8,8 +8,6 @@ on: push
env:
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
SLACK_BOT_TOKEN: ${{ secrets.SLACK_BOT_TOKEN }}
GEN_AI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
MOCK_LLM_RESPONSE: true
jobs:
playwright-tests:
@@ -198,47 +196,43 @@ jobs:
cd deployment/docker_compose
docker compose -f docker-compose.dev.yml -p danswer-stack down -v
# NOTE: Chromatic UI diff testing is currently disabled.
# We are using Playwright for local and CI testing without visual regression checks.
# Chromatic may be reintroduced in the future for UI diff testing if needed.
chromatic-tests:
name: Chromatic Tests
# chromatic-tests:
# name: Chromatic Tests
needs: playwright-tests
runs-on:
[
runs-on,
runner=32cpu-linux-x64,
disk=large,
"run-id=${{ github.run_id }}",
]
steps:
- name: Checkout code
uses: actions/checkout@v4
with:
fetch-depth: 0
# needs: playwright-tests
# runs-on:
# [
# runs-on,
# runner=32cpu-linux-x64,
# disk=large,
# "run-id=${{ github.run_id }}",
# ]
# steps:
# - name: Checkout code
# uses: actions/checkout@v4
# with:
# fetch-depth: 0
- name: Setup node
uses: actions/setup-node@v4
with:
node-version: 22
# - name: Setup node
# uses: actions/setup-node@v4
# with:
# node-version: 22
- name: Install node dependencies
working-directory: ./web
run: npm ci
# - name: Install node dependencies
# working-directory: ./web
# run: npm ci
- name: Download Playwright test results
uses: actions/download-artifact@v4
with:
name: test-results
path: ./web/test-results
# - name: Download Playwright test results
# uses: actions/download-artifact@v4
# with:
# name: test-results
# path: ./web/test-results
# - name: Run Chromatic
# uses: chromaui/action@latest
# with:
# playwright: true
# projectToken: ${{ secrets.CHROMATIC_PROJECT_TOKEN }}
# workingDir: ./web
# env:
# CHROMATIC_ARCHIVE_LOCATION: ./test-results
- name: Run Chromatic
uses: chromaui/action@latest
with:
playwright: true
projectToken: ${{ secrets.CHROMATIC_PROJECT_TOKEN }}
workingDir: ./web
env:
CHROMATIC_ARCHIVE_LOCATION: ./test-results

View File

@@ -21,10 +21,10 @@ jobs:
- name: Set up Helm
uses: azure/setup-helm@v4.2.0
with:
version: v3.17.0
version: v3.14.4
- name: Set up chart-testing
uses: helm/chart-testing-action@v2.7.0
uses: helm/chart-testing-action@v2.6.1
# even though we specify chart-dirs in ct.yaml, it isn't used by ct for the list-changed command...
- name: Run chart-testing (list-changed)
@@ -37,6 +37,22 @@ jobs:
echo "changed=true" >> "$GITHUB_OUTPUT"
fi
# rkuo: I don't think we need python?
# - name: Set up Python
# uses: actions/setup-python@v5
# with:
# python-version: '3.11'
# cache: 'pip'
# cache-dependency-path: |
# backend/requirements/default.txt
# backend/requirements/dev.txt
# backend/requirements/model_server.txt
# - run: |
# python -m pip install --upgrade pip
# pip install --retries 5 --timeout 30 -r backend/requirements/default.txt
# pip install --retries 5 --timeout 30 -r backend/requirements/dev.txt
# pip install --retries 5 --timeout 30 -r backend/requirements/model_server.txt
# lint all charts if any changes were detected
- name: Run chart-testing (lint)
if: steps.list-changed.outputs.changed == 'true'
@@ -46,7 +62,7 @@ jobs:
- name: Create kind cluster
if: steps.list-changed.outputs.changed == 'true'
uses: helm/kind-action@v1.12.0
uses: helm/kind-action@v1.10.0
- name: Run chart-testing (install)
if: steps.list-changed.outputs.changed == 'true'

View File

@@ -94,27 +94,23 @@ jobs:
cd deployment/docker_compose
ENABLE_PAID_ENTERPRISE_EDITION_FEATURES=true \
MULTI_TENANT=true \
AUTH_TYPE=cloud \
AUTH_TYPE=basic \
REQUIRE_EMAIL_VERIFICATION=false \
DISABLE_TELEMETRY=true \
IMAGE_TAG=test \
DEV_MODE=true \
docker compose -f docker-compose.multitenant-dev.yml -p onyx-stack up -d
docker compose -f docker-compose.dev.yml -p danswer-stack up -d
id: start_docker_multi_tenant
# In practice, `cloud` Auth type would require OAUTH credentials to be set.
- name: Run Multi-Tenant Integration Tests
run: |
echo "Waiting for 3 minutes to ensure API server is ready..."
sleep 180
echo "Running integration tests..."
docker run --rm --network onyx-stack_default \
docker run --rm --network danswer-stack_default \
--name test-runner \
-e POSTGRES_HOST=relational_db \
-e POSTGRES_USER=postgres \
-e POSTGRES_PASSWORD=password \
-e POSTGRES_DB=postgres \
-e POSTGRES_USE_NULL_POOL=true \
-e VESPA_HOST=index \
-e REDIS_HOST=cache \
-e API_SERVER_HOST=api_server \
@@ -123,10 +119,6 @@ jobs:
-e TEST_WEB_HOSTNAME=test-runner \
-e AUTH_TYPE=cloud \
-e MULTI_TENANT=true \
-e REQUIRE_EMAIL_VERIFICATION=false \
-e DISABLE_TELEMETRY=true \
-e IMAGE_TAG=test \
-e DEV_MODE=true \
onyxdotapp/onyx-integration:test \
/app/tests/integration/multitenant_tests
continue-on-error: true
@@ -134,38 +126,34 @@ jobs:
- name: Check multi-tenant test results
run: |
if [ ${{ steps.run_multitenant_tests.outcome }} == 'failure' ]; then
echo "Multi-tenant integration tests failed. Exiting with error."
if [ ${{ steps.run_tests.outcome }} == 'failure' ]; then
echo "Integration tests failed. Exiting with error."
exit 1
else
echo "All multi-tenant integration tests passed successfully."
echo "All integration tests passed successfully."
fi
- name: Stop multi-tenant Docker containers
run: |
cd deployment/docker_compose
docker compose -f docker-compose.multitenant-dev.yml -p onyx-stack down -v
docker compose -f docker-compose.dev.yml -p danswer-stack down -v
# NOTE: Use pre-ping/null pool to reduce flakiness due to dropped connections
- name: Start Docker containers
run: |
cd deployment/docker_compose
ENABLE_PAID_ENTERPRISE_EDITION_FEATURES=true \
AUTH_TYPE=basic \
POSTGRES_POOL_PRE_PING=true \
POSTGRES_USE_NULL_POOL=true \
REQUIRE_EMAIL_VERIFICATION=false \
DISABLE_TELEMETRY=true \
IMAGE_TAG=test \
INTEGRATION_TESTS_MODE=true \
docker compose -f docker-compose.dev.yml -p onyx-stack up -d
docker compose -f docker-compose.dev.yml -p danswer-stack up -d
id: start_docker
- name: Wait for service to be ready
run: |
echo "Starting wait-for-service script..."
docker logs -f onyx-stack-api_server-1 &
docker logs -f danswer-stack-api_server-1 &
start_time=$(date +%s)
timeout=300 # 5 minutes in seconds
@@ -195,24 +183,15 @@ jobs:
done
echo "Finished waiting for service."
- name: Start Mock Services
run: |
cd backend/tests/integration/mock_services
docker compose -f docker-compose.mock-it-services.yml \
-p mock-it-services-stack up -d
# NOTE: Use pre-ping/null to reduce flakiness due to dropped connections
- name: Run Standard Integration Tests
run: |
echo "Running integration tests..."
docker run --rm --network onyx-stack_default \
docker run --rm --network danswer-stack_default \
--name test-runner \
-e POSTGRES_HOST=relational_db \
-e POSTGRES_USER=postgres \
-e POSTGRES_PASSWORD=password \
-e POSTGRES_DB=postgres \
-e POSTGRES_POOL_PRE_PING=true \
-e POSTGRES_USE_NULL_POOL=true \
-e VESPA_HOST=index \
-e REDIS_HOST=cache \
-e API_SERVER_HOST=api_server \
@@ -222,8 +201,6 @@ jobs:
-e CONFLUENCE_USER_NAME=${CONFLUENCE_USER_NAME} \
-e CONFLUENCE_ACCESS_TOKEN=${CONFLUENCE_ACCESS_TOKEN} \
-e TEST_WEB_HOSTNAME=test-runner \
-e MOCK_CONNECTOR_SERVER_HOST=mock_connector_server \
-e MOCK_CONNECTOR_SERVER_PORT=8001 \
onyxdotapp/onyx-integration:test \
/app/tests/integration/tests \
/app/tests/integration/connector_job_tests
@@ -239,30 +216,27 @@ jobs:
echo "All integration tests passed successfully."
fi
# ------------------------------------------------------------
# Always gather logs BEFORE "down":
- name: Dump API server logs
if: always()
# save before stopping the containers so the logs can be captured
- name: Save Docker logs
if: success() || failure()
run: |
cd deployment/docker_compose
docker compose -f docker-compose.dev.yml -p onyx-stack logs --no-color api_server > $GITHUB_WORKSPACE/api_server.log || true
- name: Dump all-container logs (optional)
if: always()
run: |
cd deployment/docker_compose
docker compose -f docker-compose.dev.yml -p onyx-stack logs --no-color > $GITHUB_WORKSPACE/docker-compose.log || true
- name: Upload logs
if: always()
uses: actions/upload-artifact@v4
with:
name: docker-all-logs
path: ${{ github.workspace }}/docker-compose.log
# ------------------------------------------------------------
docker compose -f docker-compose.dev.yml -p danswer-stack logs > docker-compose.log
mv docker-compose.log ${{ github.workspace }}/docker-compose.log
- name: Stop Docker containers
if: always()
run: |
cd deployment/docker_compose
docker compose -f docker-compose.dev.yml -p onyx-stack down -v
docker compose -f docker-compose.dev.yml -p danswer-stack down -v
- name: Upload logs
if: success() || failure()
uses: actions/upload-artifact@v4
with:
name: docker-logs
path: ${{ github.workspace }}/docker-compose.log
- name: Stop Docker containers
run: |
cd deployment/docker_compose
docker compose -f docker-compose.dev.yml -p danswer-stack down -v

View File

@@ -1,29 +0,0 @@
name: Ensure PR references Linear
on:
pull_request:
types: [opened, edited, reopened, synchronize]
jobs:
linear-check:
runs-on: ubuntu-latest
steps:
- name: Check PR body for Linear link or override
env:
PR_BODY: ${{ github.event.pull_request.body }}
run: |
# Looking for "https://linear.app" in the body
if echo "$PR_BODY" | grep -qE "https://linear\.app"; then
echo "Found a Linear link. Check passed."
exit 0
fi
# Looking for a checked override: "[x] Override Linear Check"
if echo "$PR_BODY" | grep -q "\[x\].*Override Linear Check"; then
echo "Override box is checked. Check passed."
exit 0
fi
# Otherwise, fail the run
echo "No Linear link or override found in the PR description."
exit 1

View File

@@ -39,15 +39,6 @@ env:
AIRTABLE_TEST_TABLE_ID: ${{ secrets.AIRTABLE_TEST_TABLE_ID }}
AIRTABLE_TEST_TABLE_NAME: ${{ secrets.AIRTABLE_TEST_TABLE_NAME }}
AIRTABLE_ACCESS_TOKEN: ${{ secrets.AIRTABLE_ACCESS_TOKEN }}
# Sharepoint
SHAREPOINT_CLIENT_ID: ${{ secrets.SHAREPOINT_CLIENT_ID }}
SHAREPOINT_CLIENT_SECRET: ${{ secrets.SHAREPOINT_CLIENT_SECRET }}
SHAREPOINT_CLIENT_DIRECTORY_ID: ${{ secrets.SHAREPOINT_CLIENT_DIRECTORY_ID }}
SHAREPOINT_SITE: ${{ secrets.SHAREPOINT_SITE }}
# Gitbook
GITBOOK_SPACE_ID: ${{ secrets.GITBOOK_SPACE_ID }}
GITBOOK_API_KEY: ${{ secrets.GITBOOK_API_KEY }}
jobs:
connectors-check:
# See https://runs-on.com/runners/linux/
@@ -74,9 +65,7 @@ jobs:
python -m pip install --upgrade pip
pip install --retries 5 --timeout 30 -r backend/requirements/default.txt
pip install --retries 5 --timeout 30 -r backend/requirements/dev.txt
playwright install chromium
playwright install-deps chromium
- name: Run Tests
shell: script -q -e -c "bash --noprofile --norc -eo pipefail {0}"
run: py.test -o junit_family=xunit2 -xv --ff backend/tests/daily/connectors

View File

@@ -1,29 +1,18 @@
name: Model Server Tests
name: Connector Tests
on:
schedule:
# This cron expression runs the job daily at 16:00 UTC (9am PT)
- cron: "0 16 * * *"
workflow_dispatch:
inputs:
branch:
description: 'Branch to run the workflow on'
required: false
default: 'main'
env:
# Bedrock
AWS_ACCESS_KEY_ID: ${{ secrets.AWS_ACCESS_KEY_ID }}
AWS_SECRET_ACCESS_KEY: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
AWS_REGION_NAME: ${{ secrets.AWS_REGION_NAME }}
# API keys for testing
COHERE_API_KEY: ${{ secrets.COHERE_API_KEY }}
LITELLM_API_KEY: ${{ secrets.LITELLM_API_KEY }}
LITELLM_API_URL: ${{ secrets.LITELLM_API_URL }}
# OpenAI
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
AZURE_API_KEY: ${{ secrets.AZURE_API_KEY }}
AZURE_API_URL: ${{ secrets.AZURE_API_URL }}
jobs:
model-check:
@@ -37,23 +26,6 @@ jobs:
- name: Checkout code
uses: actions/checkout@v4
- name: Login to Docker Hub
uses: docker/login-action@v3
with:
username: ${{ secrets.DOCKER_USERNAME }}
password: ${{ secrets.DOCKER_TOKEN }}
# tag every docker image with "test" so that we can spin up the correct set
# of images during testing
# We don't need to build the Web Docker image since it's not yet used
# in the integration tests. We have a separate action to verify that it builds
# successfully.
- name: Pull Model Server Docker image
run: |
docker pull onyxdotapp/onyx-model-server:latest
docker tag onyxdotapp/onyx-model-server:latest onyxdotapp/onyx-model-server:test
- name: Set up Python
uses: actions/setup-python@v5
with:
@@ -69,49 +41,6 @@ jobs:
pip install --retries 5 --timeout 30 -r backend/requirements/default.txt
pip install --retries 5 --timeout 30 -r backend/requirements/dev.txt
- name: Start Docker containers
run: |
cd deployment/docker_compose
ENABLE_PAID_ENTERPRISE_EDITION_FEATURES=true \
AUTH_TYPE=basic \
REQUIRE_EMAIL_VERIFICATION=false \
DISABLE_TELEMETRY=true \
IMAGE_TAG=test \
docker compose -f docker-compose.model-server-test.yml -p onyx-stack up -d indexing_model_server
id: start_docker
- name: Wait for service to be ready
run: |
echo "Starting wait-for-service script..."
start_time=$(date +%s)
timeout=300 # 5 minutes in seconds
while true; do
current_time=$(date +%s)
elapsed_time=$((current_time - start_time))
if [ $elapsed_time -ge $timeout ]; then
echo "Timeout reached. Service did not become ready in 5 minutes."
exit 1
fi
# Use curl with error handling to ignore specific exit code 56
response=$(curl -s -o /dev/null -w "%{http_code}" http://localhost:9000/api/health || echo "curl_error")
if [ "$response" = "200" ]; then
echo "Service is ready!"
break
elif [ "$response" = "curl_error" ]; then
echo "Curl encountered an error, possibly exit code 56. Continuing to retry..."
else
echo "Service not ready yet (HTTP status $response). Retrying in 5 seconds..."
fi
sleep 5
done
echo "Finished waiting for service."
- name: Run Tests
shell: script -q -e -c "bash --noprofile --norc -eo pipefail {0}"
run: |
@@ -127,23 +56,3 @@ jobs:
-H 'Content-type: application/json' \
--data '{"text":"Scheduled Model Tests failed! Check the run at: https://github.com/${{ github.repository }}/actions/runs/${{ github.run_id }}"}' \
$SLACK_WEBHOOK
- name: Dump all-container logs (optional)
if: always()
run: |
cd deployment/docker_compose
docker compose -f docker-compose.model-server-test.yml -p onyx-stack logs --no-color > $GITHUB_WORKSPACE/docker-compose.log || true
- name: Upload logs
if: always()
uses: actions/upload-artifact@v4
with:
name: docker-all-logs
path: ${{ github.workspace }}/docker-compose.log
- name: Stop Docker containers
if: always()
run: |
cd deployment/docker_compose
docker compose -f docker-compose.model-server-test.yml -p onyx-stack down -v

View File

@@ -29,7 +29,6 @@ REQUIRE_EMAIL_VERIFICATION=False
# Set these so if you wipe the DB, you don't end up having to go through the UI every time
GEN_AI_API_KEY=<REPLACE THIS>
OPENAI_API_KEY=<REPLACE THIS>
# If answer quality isn't important for dev, use gpt-4o-mini since it's cheaper
GEN_AI_MODEL_VERSION=gpt-4o
FAST_GEN_AI_MODEL_VERSION=gpt-4o

View File

@@ -28,7 +28,6 @@
"Celery heavy",
"Celery indexing",
"Celery beat",
"Celery monitoring",
],
"presentation": {
"group": "1",
@@ -52,8 +51,7 @@
"Celery light",
"Celery heavy",
"Celery indexing",
"Celery beat",
"Celery monitoring",
"Celery beat"
],
"presentation": {
"group": "1",
@@ -205,7 +203,7 @@
"--loglevel=INFO",
"--hostname=light@%n",
"-Q",
"vespa_metadata_sync,connector_deletion,doc_permissions_upsert,checkpoint_cleanup",
"vespa_metadata_sync,connector_deletion,doc_permissions_upsert",
],
"presentation": {
"group": "2",
@@ -271,31 +269,6 @@
},
"consoleTitle": "Celery indexing Console"
},
{
"name": "Celery monitoring",
"type": "debugpy",
"request": "launch",
"module": "celery",
"cwd": "${workspaceFolder}/backend",
"envFile": "${workspaceFolder}/.vscode/.env",
"env": {},
"args": [
"-A",
"onyx.background.celery.versioned_apps.monitoring",
"worker",
"--pool=solo",
"--concurrency=1",
"--prefetch-multiplier=1",
"--loglevel=INFO",
"--hostname=monitoring@%n",
"-Q",
"monitoring",
],
"presentation": {
"group": "2",
},
"consoleTitle": "Celery monitoring Console"
},
{
"name": "Celery beat",
"type": "debugpy",

View File

@@ -17,10 +17,9 @@ Before starting, make sure the Docker Daemon is running.
1. Open the Debug view in VSCode (Cmd+Shift+D on macOS)
2. From the dropdown at the top, select "Clear and Restart External Volumes and Containers" and press the green play button
3. From the dropdown at the top, select "Run All Onyx Services" and press the green play button
4. CD into web, run "npm i" followed by npm run dev.
5. Now, you can navigate to onyx in your browser (default is http://localhost:3000) and start using the app
6. You can set breakpoints by clicking to the left of line numbers to help debug while the app is running
7. Use the debug toolbar to step through code, inspect variables, etc.
4. Now, you can navigate to onyx in your browser (default is http://localhost:3000) and start using the app
5. You can set breakpoints by clicking to the left of line numbers to help debug while the app is running
6. Use the debug toolbar to step through code, inspect variables, etc.
## Features

123
README.md
View File

@@ -24,93 +24,112 @@
</a>
</p>
<strong>[Onyx](https://www.onyx.app/)</strong> (formerly Danswer) is the AI platform connected to your company's docs, apps, and people.
Onyx provides a feature rich Chat interface and plugs into any LLM of your choice.
Keep knowledge and access controls sync-ed across over 40 connectors like Google Drive, Slack, Confluence, Salesforce, etc.
Create custom AI agents with unique prompts, knowledge, and actions that the agents can take.
Onyx can be deployed securely anywhere and for any scale - on a laptop, on-premise, or to cloud.
<strong>[Onyx](https://www.onyx.app/)</strong> (formerly Danswer) is the AI Assistant connected to your company's docs, apps, and people.
Onyx provides a Chat interface and plugs into any LLM of your choice. Onyx can be deployed anywhere and for any
scale - on a laptop, on-premise, or to cloud. Since you own the deployment, your user data and chats are fully in your
own control. Onyx is dual Licensed with most of it under MIT license and designed to be modular and easily extensible. The system also comes fully ready
for production usage with user authentication, role management (admin/basic users), chat persistence, and a UI for
configuring AI Assistants.
Onyx also serves as a Enterprise Search across all common workplace tools such as Slack, Google Drive, Confluence, etc.
By combining LLMs and team specific knowledge, Onyx becomes a subject matter expert for the team. Imagine ChatGPT if
it had access to your team's unique knowledge! It enables questions such as "A customer wants feature X, is this already
supported?" or "Where's the pull request for feature Y?"
<h3>Feature Highlights</h3>
<h3>Usage</h3>
**Deep research over your team's knowledge:**
Onyx Web App:
https://private-user-images.githubusercontent.com/32520769/414509312-48392e83-95d0-4fb5-8650-a396e05e0a32.mp4?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.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.a9D8A0sgKE9AoaoE-mfFbJ6_OKYeqaf7TZ4Han2JfW8
https://github.com/onyx-dot-app/onyx/assets/32520769/563be14c-9304-47b5-bf0a-9049c2b6f410
Or, plug Onyx into your existing Slack workflows (more integrations to come 😁):
**Use Onyx as a secure AI Chat with any LLM:**
![Onyx Chat Silent Demo](https://github.com/onyx-dot-app/onyx/releases/download/v0.21.1/OnyxChatSilentDemo.gif)
**Easily set up connectors to your apps:**
![Onyx Connector Silent Demo](https://github.com/onyx-dot-app/onyx/releases/download/v0.21.1/OnyxConnectorSilentDemo.gif)
**Access Onyx where your team already works:**
![Onyx Bot Demo](https://github.com/onyx-dot-app/onyx/releases/download/v0.21.1/OnyxBot.png)
https://github.com/onyx-dot-app/onyx/assets/25087905/3e19739b-d178-4371-9a38-011430bdec1b
For more details on the Admin UI to manage connectors and users, check out our
<strong><a href="https://www.youtube.com/watch?v=geNzY1nbCnU">Full Video Demo</a></strong>!
## Deployment
**To try it out for free and get started in seconds, check out [Onyx Cloud](https://cloud.onyx.app/signup)**.
Onyx can also be run locally (even on a laptop) or deployed on a virtual machine with a single
Onyx can easily be run locally (even on a laptop) or deployed on a virtual machine with a single
`docker compose` command. Checkout our [docs](https://docs.onyx.app/quickstart) to learn more.
We also have built-in support for high-availability/scalable deployment on Kubernetes.
References [here](https://github.com/onyx-dot-app/onyx/tree/main/deployment).
We also have built-in support for deployment on Kubernetes. Files for that can be found [here](https://github.com/onyx-dot-app/onyx/tree/main/deployment/kubernetes).
## 💃 Main Features
## 🔍 Other Notable Benefits of Onyx
- Custom deep learning models for indexing and inference time, only through Onyx + learning from user feedback.
- Flexible security features like SSO (OIDC/SAML/OAuth2), RBAC, encryption of credentials, etc.
- Knowledge curation features like document-sets, query history, usage analytics, etc.
- Scalable deployment options tested up to many tens of thousands users and hundreds of millions of documents.
- Chat UI with the ability to select documents to chat with.
- Create custom AI Assistants with different prompts and backing knowledge sets.
- Connect Onyx with LLM of your choice (self-host for a fully airgapped solution).
- Document Search + AI Answers for natural language queries.
- Connectors to all common workplace tools like Google Drive, Confluence, Slack, etc.
- Slack integration to get answers and search results directly in Slack.
## 🚧 Roadmap
- New methods in information retrieval (StructRAG, LightGraphRAG, etc.)
- Personalized Search
- Organizational understanding and ability to locate and suggest experts from your team.
- Code Search
- SQL and Structured Query Language
- Chat/Prompt sharing with specific teammates and user groups.
- Multimodal model support, chat with images, video etc.
- Choosing between LLMs and parameters during chat session.
- Tool calling and agent configurations options.
- Organizational understanding and ability to locate and suggest experts from your team.
## Other Notable Benefits of Onyx
- User Authentication with document level access management.
- Best in class Hybrid Search across all sources (BM-25 + prefix aware embedding models).
- Admin Dashboard to configure connectors, document-sets, access, etc.
- Custom deep learning models + learn from user feedback.
- Easy deployment and ability to host Onyx anywhere of your choosing.
## 🔌 Connectors
Keep knowledge and access up to sync across 40+ connectors:
Efficiently pulls the latest changes from:
- Slack
- GitHub
- Google Drive
- Confluence
- Slack
- Gmail
- Salesforce
- Microsoft Sharepoint
- Github
- Jira
- Zendesk
- Gmail
- Notion
- Gong
- Microsoft Teams
- Dropbox
- Slab
- Linear
- Productboard
- Guru
- Bookstack
- Document360
- Sharepoint
- Hubspot
- Local Files
- Websites
- And more ...
See the full list [here](https://docs.onyx.app/connectors).
## 📚 Editions
## 📚 Licensing
There are two editions of Onyx:
- Onyx Community Edition (CE) is available freely under the MIT Expat license. Simply follow the Deployment guide above.
- Onyx Enterprise Edition (EE) includes extra features that are primarily useful for larger organizations.
For feature details, check out [our website](https://www.onyx.app/pricing).
- Onyx Community Edition (CE) is available freely under the MIT Expat license. This version has ALL the core features discussed above. This is the version of Onyx you will get if you follow the Deployment guide above.
- Onyx Enterprise Edition (EE) includes extra features that are primarily useful for larger organizations. Specifically, this includes:
- Single Sign-On (SSO), with support for both SAML and OIDC
- Role-based access control
- Document permission inheritance from connected sources
- Usage analytics and query history accessible to admins
- Whitelabeling
- API key authentication
- Encryption of secrets
- Any many more! Checkout [our website](https://www.onyx.app/) for the latest.
To try the Onyx Enterprise Edition:
1. Checkout [Onyx Cloud](https://cloud.onyx.app/signup).
2. For self-hosting the Enterprise Edition, contact us at [founders@onyx.app](mailto:founders@onyx.app) or book a call with us on our [Cal](https://cal.com/team/onyx/founders).
1. Checkout our [Cloud product](https://cloud.onyx.app/signup).
2. For self-hosting, contact us at [founders@onyx.app](mailto:founders@onyx.app) or book a call with us on our [Cal](https://cal.com/team/danswer/founders).
## 💡 Contributing
Looking to contribute? Please check out the [Contribution Guide](CONTRIBUTING.md) for more details.
## ⭐Star History
[![Star History Chart](https://api.star-history.com/svg?repos=onyx-dot-app/onyx&type=Date)](https://star-history.com/#onyx-dot-app/onyx&Date)

View File

@@ -9,10 +9,8 @@ founders@onyx.app for more information. Please visit https://github.com/onyx-dot
# Default ONYX_VERSION, typically overriden during builds by GitHub Actions.
ARG ONYX_VERSION=0.8-dev
# DO_NOT_TRACK is used to disable telemetry for Unstructured
ENV ONYX_VERSION=${ONYX_VERSION} \
DANSWER_RUNNING_IN_DOCKER="true" \
DO_NOT_TRACK="true"
DANSWER_RUNNING_IN_DOCKER="true"
RUN echo "ONYX_VERSION: ${ONYX_VERSION}"
@@ -28,16 +26,14 @@ RUN apt-get update && \
curl \
zip \
ca-certificates \
libgnutls30 \
libblkid1 \
libmount1 \
libsmartcols1 \
libuuid1 \
libgnutls30=3.7.9-2+deb12u3 \
libblkid1=2.38.1-5+deb12u1 \
libmount1=2.38.1-5+deb12u1 \
libsmartcols1=2.38.1-5+deb12u1 \
libuuid1=2.38.1-5+deb12u1 \
libxmlsec1-dev \
pkg-config \
gcc \
nano \
vim && \
gcc && \
rm -rf /var/lib/apt/lists/* && \
apt-get clean
@@ -103,8 +99,7 @@ COPY ./alembic_tenants /app/alembic_tenants
COPY ./alembic.ini /app/alembic.ini
COPY supervisord.conf /usr/etc/supervisord.conf
# Escape hatch scripts
COPY ./scripts/debugging /app/scripts/debugging
# Escape hatch
COPY ./scripts/force_delete_connector_by_id.py /app/scripts/force_delete_connector_by_id.py
# Put logo in assets

View File

@@ -20,7 +20,7 @@ def upgrade() -> None:
op.add_column(
"user",
sa.Column(
"shortcut_enabled", sa.Boolean(), nullable=False, server_default="false"
"shortcut_enabled", sa.Boolean(), nullable=False, server_default="true"
),
)

View File

@@ -1,36 +0,0 @@
"""add index to index_attempt.time_created
Revision ID: 0f7ff6d75b57
Revises: 369644546676
Create Date: 2025-01-10 14:01:14.067144
"""
from alembic import op
# revision identifiers, used by Alembic.
revision = "0f7ff6d75b57"
down_revision = "fec3db967bf7"
branch_labels: None = None
depends_on: None = None
def upgrade() -> None:
op.create_index(
op.f("ix_index_attempt_status"),
"index_attempt",
["status"],
unique=False,
)
op.create_index(
op.f("ix_index_attempt_time_created"),
"index_attempt",
["time_created"],
unique=False,
)
def downgrade() -> None:
op.drop_index(op.f("ix_index_attempt_time_created"), table_name="index_attempt")
op.drop_index(op.f("ix_index_attempt_status"), table_name="index_attempt")

View File

@@ -1,27 +0,0 @@
"""Add indexes to document__tag
Revision ID: 1a03d2c2856b
Revises: 9c00a2bccb83
Create Date: 2025-02-18 10:45:13.957807
"""
from alembic import op
# revision identifiers, used by Alembic.
revision = "1a03d2c2856b"
down_revision = "9c00a2bccb83"
branch_labels: None = None
depends_on: None = None
def upgrade() -> None:
op.create_index(
op.f("ix_document__tag_tag_id"),
"document__tag",
["tag_id"],
unique=False,
)
def downgrade() -> None:
op.drop_index(op.f("ix_document__tag_tag_id"), table_name="document__tag")

View File

@@ -0,0 +1,29 @@
"""agent_doc_result_col
Revision ID: 1adf5ea20d2b
Revises: e9cf2bd7baed
Create Date: 2025-01-05 13:14:58.344316
"""
from alembic import op
import sqlalchemy as sa
from sqlalchemy.dialects import postgresql
# revision identifiers, used by Alembic.
revision = "1adf5ea20d2b"
down_revision = "e9cf2bd7baed"
branch_labels = None
depends_on = None
def upgrade() -> None:
# Add the new column with JSONB type
op.add_column(
"sub_question",
sa.Column("sub_question_doc_results", postgresql.JSONB(), nullable=True),
)
def downgrade() -> None:
# Drop the column
op.drop_column("sub_question", "sub_question_doc_results")

View File

@@ -1,32 +0,0 @@
"""set built in to default
Revision ID: 2cdeff6d8c93
Revises: f5437cc136c5
Create Date: 2025-02-11 14:57:51.308775
"""
from alembic import op
# revision identifiers, used by Alembic.
revision = "2cdeff6d8c93"
down_revision = "f5437cc136c5"
branch_labels = None
depends_on = None
def upgrade() -> None:
# Prior to this migration / point in the codebase history,
# built in personas were implicitly treated as default personas (with no option to change this)
# This migration makes that explicit
op.execute(
"""
UPDATE persona
SET is_default_persona = TRUE
WHERE builtin_persona = TRUE
"""
)
def downgrade() -> None:
pass

View File

@@ -1,36 +0,0 @@
"""add chat session specific temperature override
Revision ID: 2f80c6a2550f
Revises: 33ea50e88f24
Create Date: 2025-01-31 10:30:27.289646
"""
from alembic import op
import sqlalchemy as sa
# revision identifiers, used by Alembic.
revision = "2f80c6a2550f"
down_revision = "33ea50e88f24"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.add_column(
"chat_session", sa.Column("temperature_override", sa.Float(), nullable=True)
)
op.add_column(
"user",
sa.Column(
"temperature_override_enabled",
sa.Boolean(),
nullable=False,
server_default=sa.false(),
),
)
def downgrade() -> None:
op.drop_column("chat_session", "temperature_override")
op.drop_column("user", "temperature_override_enabled")

View File

@@ -1,80 +0,0 @@
"""foreign key input prompts
Revision ID: 33ea50e88f24
Revises: a6df6b88ef81
Create Date: 2025-01-29 10:54:22.141765
"""
from alembic import op
# revision identifiers, used by Alembic.
revision = "33ea50e88f24"
down_revision = "a6df6b88ef81"
branch_labels = None
depends_on = None
def upgrade() -> None:
# Safely drop constraints if exists
op.execute(
"""
ALTER TABLE inputprompt__user
DROP CONSTRAINT IF EXISTS inputprompt__user_input_prompt_id_fkey
"""
)
op.execute(
"""
ALTER TABLE inputprompt__user
DROP CONSTRAINT IF EXISTS inputprompt__user_user_id_fkey
"""
)
# Recreate with ON DELETE CASCADE
op.create_foreign_key(
"inputprompt__user_input_prompt_id_fkey",
"inputprompt__user",
"inputprompt",
["input_prompt_id"],
["id"],
ondelete="CASCADE",
)
op.create_foreign_key(
"inputprompt__user_user_id_fkey",
"inputprompt__user",
"user",
["user_id"],
["id"],
ondelete="CASCADE",
)
def downgrade() -> None:
# Drop the new FKs with ondelete
op.drop_constraint(
"inputprompt__user_input_prompt_id_fkey",
"inputprompt__user",
type_="foreignkey",
)
op.drop_constraint(
"inputprompt__user_user_id_fkey",
"inputprompt__user",
type_="foreignkey",
)
# Recreate them without cascading
op.create_foreign_key(
"inputprompt__user_input_prompt_id_fkey",
"inputprompt__user",
"inputprompt",
["input_prompt_id"],
["id"],
)
op.create_foreign_key(
"inputprompt__user_user_id_fkey",
"inputprompt__user",
"user",
["user_id"],
["id"],
)

View File

@@ -1,84 +0,0 @@
"""improved index
Revision ID: 3bd4c84fe72f
Revises: 8f43500ee275
Create Date: 2025-02-26 13:07:56.217791
"""
from alembic import op
# revision identifiers, used by Alembic.
revision = "3bd4c84fe72f"
down_revision = "8f43500ee275"
branch_labels = None
depends_on = None
# NOTE:
# This migration addresses issues with the previous migration (8f43500ee275) which caused
# an outage by creating an index without using CONCURRENTLY. This migration:
#
# 1. Creates more efficient full-text search capabilities using tsvector columns and GIN indexes
# 2. Uses CONCURRENTLY for all index creation to prevent table locking
# 3. Explicitly manages transactions with COMMIT statements to allow CONCURRENTLY to work
# (see: https://www.postgresql.org/docs/9.4/sql-createindex.html#SQL-CREATEINDEX-CONCURRENTLY)
# (see: https://github.com/sqlalchemy/alembic/issues/277)
# 4. Adds indexes to both chat_message and chat_session tables for comprehensive search
def upgrade() -> None:
# Create a GIN index for full-text search on chat_message.message
op.execute(
"""
ALTER TABLE chat_message
ADD COLUMN message_tsv tsvector
GENERATED ALWAYS AS (to_tsvector('english', message)) STORED;
"""
)
# Commit the current transaction before creating concurrent indexes
op.execute("COMMIT")
op.execute(
"""
CREATE INDEX CONCURRENTLY IF NOT EXISTS idx_chat_message_tsv
ON chat_message
USING GIN (message_tsv)
"""
)
# Also add a stored tsvector column for chat_session.description
op.execute(
"""
ALTER TABLE chat_session
ADD COLUMN description_tsv tsvector
GENERATED ALWAYS AS (to_tsvector('english', coalesce(description, ''))) STORED;
"""
)
# Commit again before creating the second concurrent index
op.execute("COMMIT")
op.execute(
"""
CREATE INDEX CONCURRENTLY IF NOT EXISTS idx_chat_session_desc_tsv
ON chat_session
USING GIN (description_tsv)
"""
)
def downgrade() -> None:
# Drop the indexes first (use CONCURRENTLY for dropping too)
op.execute("COMMIT")
op.execute("DROP INDEX CONCURRENTLY IF EXISTS idx_chat_message_tsv;")
op.execute("COMMIT")
op.execute("DROP INDEX CONCURRENTLY IF EXISTS idx_chat_session_desc_tsv;")
# Then drop the columns
op.execute("ALTER TABLE chat_message DROP COLUMN IF EXISTS message_tsv;")
op.execute("ALTER TABLE chat_session DROP COLUMN IF EXISTS description_tsv;")
op.execute("DROP INDEX IF EXISTS idx_chat_message_message_lower;")

View File

@@ -41,7 +41,6 @@ def upgrade() -> None:
sa.Column(
"user_id", fastapi_users_db_sqlalchemy.generics.GUID(), nullable=False
),
sa.Column("disabled", sa.Boolean(), nullable=False, default=False),
sa.ForeignKeyConstraint(
["input_prompt_id"],
["inputprompt.id"],

View File

@@ -40,6 +40,6 @@ def upgrade() -> None:
def downgrade() -> None:
op.drop_constraint("persona_category_id_fkey", "persona", type_="foreignkey")
op.drop_constraint("fk_persona_category", "persona", type_="foreignkey")
op.drop_column("persona", "category_id")
op.drop_table("persona_category")

View File

@@ -1,37 +0,0 @@
"""lowercase_user_emails
Revision ID: 4d58345da04a
Revises: f1ca58b2f2ec
Create Date: 2025-01-29 07:48:46.784041
"""
from alembic import op
from sqlalchemy.sql import text
# revision identifiers, used by Alembic.
revision = "4d58345da04a"
down_revision = "f1ca58b2f2ec"
branch_labels = None
depends_on = None
def upgrade() -> None:
# Get database connection
connection = op.get_bind()
# Update all user emails to lowercase
connection.execute(
text(
"""
UPDATE "user"
SET email = LOWER(email)
WHERE email != LOWER(email)
"""
)
)
def downgrade() -> None:
# Cannot restore original case of emails
pass

View File

@@ -5,6 +5,7 @@ Revises: 47e5bef3a1d7
Create Date: 2024-11-06 13:15:53.302644
"""
import logging
from typing import cast
from alembic import op
import sqlalchemy as sa
@@ -19,8 +20,13 @@ down_revision = "47e5bef3a1d7"
branch_labels: None = None
depends_on: None = None
# Configure logging
logger = logging.getLogger("alembic.runtime.migration")
logger.setLevel(logging.INFO)
def upgrade() -> None:
logger.info(f"{revision}: create_table: slack_bot")
# Create new slack_bot table
op.create_table(
"slack_bot",
@@ -57,6 +63,7 @@ def upgrade() -> None:
)
# Handle existing Slack bot tokens first
logger.info(f"{revision}: Checking for existing Slack bot.")
bot_token = None
app_token = None
first_row_id = None
@@ -64,12 +71,15 @@ def upgrade() -> None:
try:
tokens = cast(dict, get_kv_store().load("slack_bot_tokens_config_key"))
except Exception:
logger.warning("No existing Slack bot tokens found.")
tokens = {}
bot_token = tokens.get("bot_token")
app_token = tokens.get("app_token")
if bot_token and app_token:
logger.info(f"{revision}: Found bot and app tokens.")
session = Session(bind=op.get_bind())
new_slack_bot = SlackBot(
name="Slack Bot (Migrated)",
@@ -160,9 +170,10 @@ def upgrade() -> None:
# Clean up old tokens if they existed
try:
if bot_token and app_token:
logger.info(f"{revision}: Removing old bot and app tokens.")
get_kv_store().delete("slack_bot_tokens_config_key")
except Exception:
pass
logger.warning("tried to delete tokens in dynamic config but failed")
# Rename the table
op.rename_table(
"slack_bot_config__standard_answer_category",
@@ -179,6 +190,8 @@ def upgrade() -> None:
# Drop the table with CASCADE to handle dependent objects
op.execute("DROP TABLE slack_bot_config CASCADE")
logger.info(f"{revision}: Migration complete.")
def downgrade() -> None:
# Recreate the old slack_bot_config table
@@ -260,7 +273,7 @@ def downgrade() -> None:
}
get_kv_store().store("slack_bot_tokens_config_key", tokens)
except Exception:
pass
logger.warning("Failed to save tokens back to KV store")
# Drop the new tables in reverse order
op.drop_table("slack_channel_config")

View File

@@ -32,7 +32,6 @@ def upgrade() -> None:
sa.ForeignKeyConstraint(
["persona_label_id"],
["persona_label.id"],
ondelete="CASCADE",
),
sa.PrimaryKeyConstraint("persona_id", "persona_label_id"),
)

View File

@@ -1,32 +0,0 @@
"""add index
Revision ID: 8f43500ee275
Revises: da42808081e3
Create Date: 2025-02-24 17:35:33.072714
"""
from alembic import op
# revision identifiers, used by Alembic.
revision = "8f43500ee275"
down_revision = "da42808081e3"
branch_labels = None
depends_on = None
def upgrade() -> None:
# Create a basic index on the lowercase message column for direct text matching
# Limit to 1500 characters to stay well under the 2856 byte limit of btree version 4
# op.execute(
# """
# CREATE INDEX idx_chat_message_message_lower
# ON chat_message (LOWER(substring(message, 1, 1500)))
# """
# )
pass
def downgrade() -> None:
# Drop the index
op.execute("DROP INDEX IF EXISTS idx_chat_message_message_lower;")

View File

@@ -0,0 +1,35 @@
"""agent_metric_col_rename__s
Revision ID: 925b58bd75b6
Revises: 9787be927e58
Create Date: 2025-01-06 11:20:26.752441
"""
from alembic import op
# revision identifiers, used by Alembic.
revision = "925b58bd75b6"
down_revision = "9787be927e58"
branch_labels = None
depends_on = None
def upgrade() -> None:
# Rename columns using PostgreSQL syntax
op.alter_column(
"agent__search_metrics", "base_duration_s", new_column_name="base_duration__s"
)
op.alter_column(
"agent__search_metrics", "full_duration_s", new_column_name="full_duration__s"
)
def downgrade() -> None:
# Revert the column renames
op.alter_column(
"agent__search_metrics", "base_duration__s", new_column_name="base_duration_s"
)
op.alter_column(
"agent__search_metrics", "full_duration__s", new_column_name="full_duration_s"
)

View File

@@ -0,0 +1,25 @@
"""agent_metric_table_renames__agent__
Revision ID: 9787be927e58
Revises: bceb76d618ec
Create Date: 2025-01-06 11:01:44.210160
"""
from alembic import op
# revision identifiers, used by Alembic.
revision = "9787be927e58"
down_revision = "bceb76d618ec"
branch_labels = None
depends_on = None
def upgrade() -> None:
# Rename table from agent_search_metrics to agent__search_metrics
op.rename_table("agent_search_metrics", "agent__search_metrics")
def downgrade() -> None:
# Rename table back from agent__search_metrics to agent_search_metrics
op.rename_table("agent__search_metrics", "agent_search_metrics")

View File

@@ -1,72 +0,0 @@
"""Add SyncRecord
Revision ID: 97dbb53fa8c8
Revises: 369644546676
Create Date: 2025-01-11 19:39:50.426302
"""
from alembic import op
import sqlalchemy as sa
# revision identifiers, used by Alembic.
revision = "97dbb53fa8c8"
down_revision = "be2ab2aa50ee"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.create_table(
"sync_record",
sa.Column("id", sa.Integer(), nullable=False),
sa.Column("entity_id", sa.Integer(), nullable=False),
sa.Column(
"sync_type",
sa.Enum(
"DOCUMENT_SET",
"USER_GROUP",
"CONNECTOR_DELETION",
name="synctype",
native_enum=False,
length=40,
),
nullable=False,
),
sa.Column(
"sync_status",
sa.Enum(
"IN_PROGRESS",
"SUCCESS",
"FAILED",
"CANCELED",
name="syncstatus",
native_enum=False,
length=40,
),
nullable=False,
),
sa.Column("num_docs_synced", sa.Integer(), nullable=False),
sa.Column("sync_start_time", sa.DateTime(timezone=True), nullable=False),
sa.Column("sync_end_time", sa.DateTime(timezone=True), nullable=True),
sa.PrimaryKeyConstraint("id"),
)
# Add index for fetch_latest_sync_record query
op.create_index(
"ix_sync_record_entity_id_sync_type_sync_start_time",
"sync_record",
["entity_id", "sync_type", "sync_start_time"],
)
# Add index for cleanup_sync_records query
op.create_index(
"ix_sync_record_entity_id_sync_type_sync_status",
"sync_record",
["entity_id", "sync_type", "sync_status"],
)
def downgrade() -> None:
op.drop_index("ix_sync_record_entity_id_sync_type_sync_status")
op.drop_index("ix_sync_record_entity_id_sync_type_sync_start_time")
op.drop_table("sync_record")

View File

@@ -1,25 +1,24 @@
"""agent_tracking
Revision ID: 98a5008d8711
Revises: 2f80c6a2550f
Create Date: 2025-01-29 17:00:00.000001
Revises: 027381bce97c
Create Date: 2025-01-04 14:41:52.732238
"""
from alembic import op
import sqlalchemy as sa
from sqlalchemy.dialects import postgresql
from sqlalchemy.dialects.postgresql import UUID
# revision identifiers, used by Alembic.
revision = "98a5008d8711"
down_revision = "2f80c6a2550f"
down_revision = "027381bce97c"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.create_table(
"agent__search_metrics",
"agent_search_metrics",
sa.Column("id", sa.Integer(), nullable=False),
sa.Column("user_id", postgresql.UUID(as_uuid=True), nullable=True),
sa.Column("persona_id", sa.Integer(), nullable=True),
@@ -38,70 +37,6 @@ def upgrade() -> None:
sa.PrimaryKeyConstraint("id"),
)
# Create sub_question table
op.create_table(
"agent__sub_question",
sa.Column("id", sa.Integer, primary_key=True),
sa.Column("primary_question_id", sa.Integer, sa.ForeignKey("chat_message.id")),
sa.Column(
"chat_session_id", UUID(as_uuid=True), sa.ForeignKey("chat_session.id")
),
sa.Column("sub_question", sa.Text),
sa.Column(
"time_created", sa.DateTime(timezone=True), server_default=sa.func.now()
),
sa.Column("sub_answer", sa.Text),
sa.Column("sub_question_doc_results", postgresql.JSONB(), nullable=True),
sa.Column("level", sa.Integer(), nullable=False),
sa.Column("level_question_num", sa.Integer(), nullable=False),
)
# Create sub_query table
op.create_table(
"agent__sub_query",
sa.Column("id", sa.Integer, primary_key=True),
sa.Column(
"parent_question_id", sa.Integer, sa.ForeignKey("agent__sub_question.id")
),
sa.Column(
"chat_session_id", UUID(as_uuid=True), sa.ForeignKey("chat_session.id")
),
sa.Column("sub_query", sa.Text),
sa.Column(
"time_created", sa.DateTime(timezone=True), server_default=sa.func.now()
),
)
# Create sub_query__search_doc association table
op.create_table(
"agent__sub_query__search_doc",
sa.Column(
"sub_query_id",
sa.Integer,
sa.ForeignKey("agent__sub_query.id"),
primary_key=True,
),
sa.Column(
"search_doc_id",
sa.Integer,
sa.ForeignKey("search_doc.id"),
primary_key=True,
),
)
op.add_column(
"chat_message",
sa.Column(
"refined_answer_improvement",
sa.Boolean(),
nullable=True,
),
)
def downgrade() -> None:
op.drop_column("chat_message", "refined_answer_improvement")
op.drop_table("agent__sub_query__search_doc")
op.drop_table("agent__sub_query")
op.drop_table("agent__sub_question")
op.drop_table("agent__search_metrics")
op.drop_table("agent_search_metrics")

View File

@@ -1,43 +0,0 @@
"""chat_message_agentic
Revision ID: 9c00a2bccb83
Revises: b7a7eee5aa15
Create Date: 2025-02-17 11:15:43.081150
"""
from alembic import op
import sqlalchemy as sa
# revision identifiers, used by Alembic.
revision = "9c00a2bccb83"
down_revision = "b7a7eee5aa15"
branch_labels = None
depends_on = None
def upgrade() -> None:
# First add the column as nullable
op.add_column("chat_message", sa.Column("is_agentic", sa.Boolean(), nullable=True))
# Update existing rows based on presence of SubQuestions
op.execute(
"""
UPDATE chat_message
SET is_agentic = EXISTS (
SELECT 1
FROM agent__sub_question
WHERE agent__sub_question.primary_question_id = chat_message.id
)
WHERE is_agentic IS NULL
"""
)
# Make the column non-nullable with a default value of False
op.alter_column(
"chat_message", "is_agentic", nullable=False, server_default=sa.text("false")
)
def downgrade() -> None:
op.drop_column("chat_message", "is_agentic")

View File

@@ -1,29 +0,0 @@
"""remove recent assistants
Revision ID: a6df6b88ef81
Revises: 4d58345da04a
Create Date: 2025-01-29 10:25:52.790407
"""
from alembic import op
import sqlalchemy as sa
from sqlalchemy.dialects import postgresql
# revision identifiers, used by Alembic.
revision = "a6df6b88ef81"
down_revision = "4d58345da04a"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.drop_column("user", "recent_assistants")
def downgrade() -> None:
op.add_column(
"user",
sa.Column(
"recent_assistants", postgresql.JSONB(), server_default="[]", nullable=False
),
)

View File

@@ -1,29 +0,0 @@
"""remove inactive ccpair status on downgrade
Revision ID: acaab4ef4507
Revises: b388730a2899
Create Date: 2025-02-16 18:21:41.330212
"""
from alembic import op
from onyx.db.models import ConnectorCredentialPair
from onyx.db.enums import ConnectorCredentialPairStatus
from sqlalchemy import update
# revision identifiers, used by Alembic.
revision = "acaab4ef4507"
down_revision = "b388730a2899"
branch_labels = None
depends_on = None
def upgrade() -> None:
pass
def downgrade() -> None:
op.execute(
update(ConnectorCredentialPair)
.where(ConnectorCredentialPair.status == ConnectorCredentialPairStatus.INVALID)
.values(status=ConnectorCredentialPairStatus.ACTIVE)
)

View File

@@ -1,7 +1,7 @@
"""add pinned assistants
Revision ID: aeda5f2df4f6
Revises: c5eae4a75a1b
Revises: 369644546676
Create Date: 2025-01-09 16:04:10.770636
"""
@@ -11,7 +11,7 @@ from sqlalchemy.dialects import postgresql
# revision identifiers, used by Alembic.
revision = "aeda5f2df4f6"
down_revision = "c5eae4a75a1b"
down_revision = "369644546676"
branch_labels = None
depends_on = None

View File

@@ -1,31 +0,0 @@
"""nullable preferences
Revision ID: b388730a2899
Revises: 1a03d2c2856b
Create Date: 2025-02-17 18:49:22.643902
"""
from alembic import op
# revision identifiers, used by Alembic.
revision = "b388730a2899"
down_revision = "1a03d2c2856b"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.alter_column("user", "temperature_override_enabled", nullable=True)
op.alter_column("user", "auto_scroll", nullable=True)
def downgrade() -> None:
# Ensure no null values before making columns non-nullable
op.execute(
'UPDATE "user" SET temperature_override_enabled = false WHERE temperature_override_enabled IS NULL'
)
op.execute('UPDATE "user" SET auto_scroll = false WHERE auto_scroll IS NULL')
op.alter_column("user", "temperature_override_enabled", nullable=False)
op.alter_column("user", "auto_scroll", nullable=False)

View File

@@ -1,124 +0,0 @@
"""Add checkpointing/failure handling
Revision ID: b7a7eee5aa15
Revises: f39c5794c10a
Create Date: 2025-01-24 15:17:36.763172
"""
from alembic import op
import sqlalchemy as sa
from sqlalchemy.dialects import postgresql
# revision identifiers, used by Alembic.
revision = "b7a7eee5aa15"
down_revision = "f39c5794c10a"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.add_column(
"index_attempt",
sa.Column("checkpoint_pointer", sa.String(), nullable=True),
)
op.add_column(
"index_attempt",
sa.Column("poll_range_start", sa.DateTime(timezone=True), nullable=True),
)
op.add_column(
"index_attempt",
sa.Column("poll_range_end", sa.DateTime(timezone=True), nullable=True),
)
op.create_index(
"ix_index_attempt_cc_pair_settings_poll",
"index_attempt",
[
"connector_credential_pair_id",
"search_settings_id",
"status",
sa.text("time_updated DESC"),
],
)
# Drop the old IndexAttemptError table
op.drop_index("index_attempt_id", table_name="index_attempt_errors")
op.drop_table("index_attempt_errors")
# Create the new version of the table
op.create_table(
"index_attempt_errors",
sa.Column("id", sa.Integer(), primary_key=True),
sa.Column("index_attempt_id", sa.Integer(), nullable=False),
sa.Column("connector_credential_pair_id", sa.Integer(), nullable=False),
sa.Column("document_id", sa.String(), nullable=True),
sa.Column("document_link", sa.String(), nullable=True),
sa.Column("entity_id", sa.String(), nullable=True),
sa.Column("failed_time_range_start", sa.DateTime(timezone=True), nullable=True),
sa.Column("failed_time_range_end", sa.DateTime(timezone=True), nullable=True),
sa.Column("failure_message", sa.Text(), nullable=False),
sa.Column("is_resolved", sa.Boolean(), nullable=False, default=False),
sa.Column(
"time_created",
sa.DateTime(timezone=True),
server_default=sa.text("now()"),
nullable=False,
),
sa.ForeignKeyConstraint(
["index_attempt_id"],
["index_attempt.id"],
),
sa.ForeignKeyConstraint(
["connector_credential_pair_id"],
["connector_credential_pair.id"],
),
)
def downgrade() -> None:
op.execute("SET lock_timeout = '5s'")
# try a few times to drop the table, this has been observed to fail due to other locks
# blocking the drop
NUM_TRIES = 10
for i in range(NUM_TRIES):
try:
op.drop_table("index_attempt_errors")
break
except Exception as e:
if i == NUM_TRIES - 1:
raise e
print(f"Error dropping table: {e}. Retrying...")
op.execute("SET lock_timeout = DEFAULT")
# Recreate the old IndexAttemptError table
op.create_table(
"index_attempt_errors",
sa.Column("id", sa.Integer(), primary_key=True),
sa.Column("index_attempt_id", sa.Integer(), nullable=True),
sa.Column("batch", sa.Integer(), nullable=True),
sa.Column("doc_summaries", postgresql.JSONB(), nullable=False),
sa.Column("error_msg", sa.Text(), nullable=True),
sa.Column("traceback", sa.Text(), nullable=True),
sa.Column(
"time_created",
sa.DateTime(timezone=True),
server_default=sa.text("now()"),
),
sa.ForeignKeyConstraint(
["index_attempt_id"],
["index_attempt.id"],
),
)
op.create_index(
"index_attempt_id",
"index_attempt_errors",
["time_created"],
)
op.drop_index("ix_index_attempt_cc_pair_settings_poll")
op.drop_column("index_attempt", "checkpoint_pointer")
op.drop_column("index_attempt", "poll_range_start")
op.drop_column("index_attempt", "poll_range_end")

View File

@@ -0,0 +1,84 @@
"""agent_table_renames__agent__
Revision ID: bceb76d618ec
Revises: c0132518a25b
Create Date: 2025-01-06 10:50:48.109285
"""
from alembic import op
# revision identifiers, used by Alembic.
revision = "bceb76d618ec"
down_revision = "c0132518a25b"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.drop_constraint(
"sub_query__search_doc_sub_query_id_fkey",
"sub_query__search_doc",
type_="foreignkey",
)
op.drop_constraint(
"sub_query__search_doc_search_doc_id_fkey",
"sub_query__search_doc",
type_="foreignkey",
)
# Rename tables
op.rename_table("sub_query", "agent__sub_query")
op.rename_table("sub_question", "agent__sub_question")
op.rename_table("sub_query__search_doc", "agent__sub_query__search_doc")
# Update both foreign key constraints for agent__sub_query__search_doc
# Create new foreign keys with updated names
op.create_foreign_key(
"agent__sub_query__search_doc_sub_query_id_fkey",
"agent__sub_query__search_doc",
"agent__sub_query",
["sub_query_id"],
["id"],
)
op.create_foreign_key(
"agent__sub_query__search_doc_search_doc_id_fkey",
"agent__sub_query__search_doc",
"search_doc", # This table name doesn't change
["search_doc_id"],
["id"],
)
def downgrade() -> None:
# Update foreign key constraints for sub_query__search_doc
op.drop_constraint(
"agent__sub_query__search_doc_sub_query_id_fkey",
"agent__sub_query__search_doc",
type_="foreignkey",
)
op.drop_constraint(
"agent__sub_query__search_doc_search_doc_id_fkey",
"agent__sub_query__search_doc",
type_="foreignkey",
)
# Rename tables back
op.rename_table("agent__sub_query__search_doc", "sub_query__search_doc")
op.rename_table("agent__sub_question", "sub_question")
op.rename_table("agent__sub_query", "sub_query")
op.create_foreign_key(
"sub_query__search_doc_sub_query_id_fkey",
"sub_query__search_doc",
"sub_query",
["sub_query_id"],
["id"],
)
op.create_foreign_key(
"sub_query__search_doc_search_doc_id_fkey",
"sub_query__search_doc",
"search_doc", # This table name doesn't change
["search_doc_id"],
["id"],
)

View File

@@ -1,38 +0,0 @@
"""fix_capitalization
Revision ID: be2ab2aa50ee
Revises: 369644546676
Create Date: 2025-01-10 13:13:26.228960
"""
from alembic import op
# revision identifiers, used by Alembic.
revision = "be2ab2aa50ee"
down_revision = "369644546676"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.execute(
"""
UPDATE document
SET
external_user_group_ids = ARRAY(
SELECT LOWER(unnest(external_user_group_ids))
),
last_modified = NOW()
WHERE
external_user_group_ids IS NOT NULL
AND external_user_group_ids::text[] <> ARRAY(
SELECT LOWER(unnest(external_user_group_ids))
)::text[]
"""
)
def downgrade() -> None:
# No way to cleanly persist the bad state through an upgrade/downgrade
# cycle, so we just pass
pass

View File

@@ -0,0 +1,40 @@
"""agent_table_changes_rename_level
Revision ID: c0132518a25b
Revises: 1adf5ea20d2b
Create Date: 2025-01-05 16:38:37.660152
"""
from alembic import op
import sqlalchemy as sa
# revision identifiers, used by Alembic.
revision = "c0132518a25b"
down_revision = "1adf5ea20d2b"
branch_labels = None
depends_on = None
def upgrade() -> None:
# Add level and level_question_nr columns with NOT NULL constraint
op.add_column(
"sub_question",
sa.Column("level", sa.Integer(), nullable=False, server_default="0"),
)
op.add_column(
"sub_question",
sa.Column(
"level_question_nr", sa.Integer(), nullable=False, server_default="0"
),
)
# Remove the server_default after the columns are created
op.alter_column("sub_question", "level", server_default=None)
op.alter_column("sub_question", "level_question_nr", server_default=None)
def downgrade() -> None:
# Remove the columns
op.drop_column("sub_question", "level_question_nr")
op.drop_column("sub_question", "level")

View File

@@ -1,36 +0,0 @@
"""Add chat_message__standard_answer table
Revision ID: c5eae4a75a1b
Revises: 0f7ff6d75b57
Create Date: 2025-01-15 14:08:49.688998
"""
from alembic import op
import sqlalchemy as sa
# revision identifiers, used by Alembic.
revision = "c5eae4a75a1b"
down_revision = "0f7ff6d75b57"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.create_table(
"chat_message__standard_answer",
sa.Column("chat_message_id", sa.Integer(), nullable=False),
sa.Column("standard_answer_id", sa.Integer(), nullable=False),
sa.ForeignKeyConstraint(
["chat_message_id"],
["chat_message.id"],
),
sa.ForeignKeyConstraint(
["standard_answer_id"],
["standard_answer.id"],
),
sa.PrimaryKeyConstraint("chat_message_id", "standard_answer_id"),
)
def downgrade() -> None:
op.drop_table("chat_message__standard_answer")

View File

@@ -1,48 +0,0 @@
"""Add has_been_indexed to DocumentByConnectorCredentialPair
Revision ID: c7bf5721733e
Revises: fec3db967bf7
Create Date: 2025-01-13 12:39:05.831693
"""
from alembic import op
import sqlalchemy as sa
# revision identifiers, used by Alembic.
revision = "c7bf5721733e"
down_revision = "027381bce97c"
branch_labels = None
depends_on = None
def upgrade() -> None:
# assume all existing rows have been indexed, no better approach
op.add_column(
"document_by_connector_credential_pair",
sa.Column("has_been_indexed", sa.Boolean(), nullable=True),
)
op.execute(
"UPDATE document_by_connector_credential_pair SET has_been_indexed = TRUE"
)
op.alter_column(
"document_by_connector_credential_pair",
"has_been_indexed",
nullable=False,
)
# Add index to optimize get_document_counts_for_cc_pairs query pattern
op.create_index(
"idx_document_cc_pair_counts",
"document_by_connector_credential_pair",
["connector_id", "credential_id", "has_been_indexed"],
unique=False,
)
def downgrade() -> None:
# Remove the index first before removing the column
op.drop_index(
"idx_document_cc_pair_counts",
table_name="document_by_connector_credential_pair",
)
op.drop_column("document_by_connector_credential_pair", "has_been_indexed")

View File

@@ -1,120 +0,0 @@
"""migrate jira connectors to new format
Revision ID: da42808081e3
Revises: f13db29f3101
Create Date: 2025-02-24 11:24:54.396040
"""
from alembic import op
import sqlalchemy as sa
import json
from onyx.configs.constants import DocumentSource
from onyx.connectors.onyx_jira.utils import extract_jira_project
# revision identifiers, used by Alembic.
revision = "da42808081e3"
down_revision = "f13db29f3101"
branch_labels = None
depends_on = None
def upgrade() -> None:
# Get all Jira connectors
conn = op.get_bind()
# First get all Jira connectors
jira_connectors = conn.execute(
sa.text(
"""
SELECT id, connector_specific_config
FROM connector
WHERE source = :source
"""
),
{"source": DocumentSource.JIRA.value.upper()},
).fetchall()
# Update each connector's config
for connector_id, old_config in jira_connectors:
if not old_config:
continue
# Extract project key from URL if it exists
new_config: dict[str, str | None] = {}
if project_url := old_config.get("jira_project_url"):
# Parse the URL to get base and project
try:
jira_base, project_key = extract_jira_project(project_url)
new_config = {"jira_base_url": jira_base, "project_key": project_key}
except ValueError:
# If URL parsing fails, just use the URL as the base
new_config = {
"jira_base_url": project_url.split("/projects/")[0],
"project_key": None,
}
else:
# For connectors without a project URL, we need admin intervention
# Mark these for review
print(
f"WARNING: Jira connector {connector_id} has no project URL configured"
)
continue
# Update the connector config
conn.execute(
sa.text(
"""
UPDATE connector
SET connector_specific_config = :new_config
WHERE id = :id
"""
),
{"id": connector_id, "new_config": json.dumps(new_config)},
)
def downgrade() -> None:
# Get all Jira connectors
conn = op.get_bind()
# First get all Jira connectors
jira_connectors = conn.execute(
sa.text(
"""
SELECT id, connector_specific_config
FROM connector
WHERE source = :source
"""
),
{"source": DocumentSource.JIRA.value.upper()},
).fetchall()
# Update each connector's config back to the old format
for connector_id, new_config in jira_connectors:
if not new_config:
continue
old_config = {}
base_url = new_config.get("jira_base_url")
project_key = new_config.get("project_key")
if base_url and project_key:
old_config = {"jira_project_url": f"{base_url}/projects/{project_key}"}
elif base_url:
old_config = {"jira_project_url": base_url}
else:
continue
# Update the connector config
conn.execute(
sa.text(
"""
UPDATE connector
SET connector_specific_config = :old_config
WHERE id = :id
"""
),
{"id": connector_id, "old_config": old_config},
)

View File

@@ -0,0 +1,68 @@
"""create pro search persistence tables
Revision ID: e9cf2bd7baed
Revises: 98a5008d8711
Create Date: 2025-01-02 17:55:56.544246
"""
from alembic import op
import sqlalchemy as sa
from sqlalchemy.dialects.postgresql import UUID
# revision identifiers, used by Alembic.
revision = "e9cf2bd7baed"
down_revision = "98a5008d8711"
branch_labels = None
depends_on = None
def upgrade() -> None:
# Create sub_question table
op.create_table(
"sub_question",
sa.Column("id", sa.Integer, primary_key=True),
sa.Column("primary_question_id", sa.Integer, sa.ForeignKey("chat_message.id")),
sa.Column(
"chat_session_id", UUID(as_uuid=True), sa.ForeignKey("chat_session.id")
),
sa.Column("sub_question", sa.Text),
sa.Column(
"time_created", sa.DateTime(timezone=True), server_default=sa.func.now()
),
sa.Column("sub_answer", sa.Text),
)
# Create sub_query table
op.create_table(
"sub_query",
sa.Column("id", sa.Integer, primary_key=True),
sa.Column("parent_question_id", sa.Integer, sa.ForeignKey("sub_question.id")),
sa.Column(
"chat_session_id", UUID(as_uuid=True), sa.ForeignKey("chat_session.id")
),
sa.Column("sub_query", sa.Text),
sa.Column(
"time_created", sa.DateTime(timezone=True), server_default=sa.func.now()
),
)
# Create sub_query__search_doc association table
op.create_table(
"sub_query__search_doc",
sa.Column(
"sub_query_id", sa.Integer, sa.ForeignKey("sub_query.id"), primary_key=True
),
sa.Column(
"search_doc_id",
sa.Integer,
sa.ForeignKey("search_doc.id"),
primary_key=True,
),
)
def downgrade() -> None:
op.drop_table("sub_query__search_doc")
op.drop_table("sub_query")
op.drop_table("sub_question")

View File

@@ -1,80 +0,0 @@
"""add default slack channel config
Revision ID: eaa3b5593925
Revises: 98a5008d8711
Create Date: 2025-02-03 18:07:56.552526
"""
from alembic import op
import sqlalchemy as sa
# revision identifiers, used by Alembic.
revision = "eaa3b5593925"
down_revision = "98a5008d8711"
branch_labels = None
depends_on = None
def upgrade() -> None:
# Add is_default column
op.add_column(
"slack_channel_config",
sa.Column("is_default", sa.Boolean(), nullable=False, server_default="false"),
)
op.create_index(
"ix_slack_channel_config_slack_bot_id_default",
"slack_channel_config",
["slack_bot_id", "is_default"],
unique=True,
postgresql_where=sa.text("is_default IS TRUE"),
)
# Create default channel configs for existing slack bots without one
conn = op.get_bind()
slack_bots = conn.execute(sa.text("SELECT id FROM slack_bot")).fetchall()
for slack_bot in slack_bots:
slack_bot_id = slack_bot[0]
existing_default = conn.execute(
sa.text(
"SELECT id FROM slack_channel_config WHERE slack_bot_id = :bot_id AND is_default = TRUE"
),
{"bot_id": slack_bot_id},
).fetchone()
if not existing_default:
conn.execute(
sa.text(
"""
INSERT INTO slack_channel_config (
slack_bot_id, persona_id, channel_config, enable_auto_filters, is_default
) VALUES (
:bot_id, NULL,
'{"channel_name": null, '
'"respond_member_group_list": [], '
'"answer_filters": [], '
'"follow_up_tags": [], '
'"respond_tag_only": true}',
FALSE, TRUE
)
"""
),
{"bot_id": slack_bot_id},
)
def downgrade() -> None:
# Delete default slack channel configs
conn = op.get_bind()
conn.execute(sa.text("DELETE FROM slack_channel_config WHERE is_default = TRUE"))
# Remove index
op.drop_index(
"ix_slack_channel_config_slack_bot_id_default",
table_name="slack_channel_config",
)
# Remove is_default column
op.drop_column("slack_channel_config", "is_default")

View File

@@ -1,36 +0,0 @@
"""force lowercase all users
Revision ID: f11b408e39d3
Revises: 3bd4c84fe72f
Create Date: 2025-02-26 17:04:55.683500
"""
# revision identifiers, used by Alembic.
revision = "f11b408e39d3"
down_revision = "3bd4c84fe72f"
branch_labels = None
depends_on = None
def upgrade() -> None:
# 1) Convert all existing user emails to lowercase
from alembic import op
op.execute(
"""
UPDATE "user"
SET email = LOWER(email)
"""
)
# 2) Add a check constraint to ensure emails are always lowercase
op.create_check_constraint("ensure_lowercase_email", "user", "email = LOWER(email)")
def downgrade() -> None:
# Drop the check constraint
from alembic import op
op.drop_constraint("ensure_lowercase_email", "user", type_="check")

View File

@@ -1,27 +0,0 @@
"""Add composite index for last_modified and last_synced to document
Revision ID: f13db29f3101
Revises: b388730a2899
Create Date: 2025-02-18 22:48:11.511389
"""
from alembic import op
# revision identifiers, used by Alembic.
revision = "f13db29f3101"
down_revision = "acaab4ef4507"
branch_labels: str | None = None
depends_on: str | None = None
def upgrade() -> None:
op.create_index(
"ix_document_sync_status",
"document",
["last_modified", "last_synced"],
unique=False,
)
def downgrade() -> None:
op.drop_index("ix_document_sync_status", table_name="document")

View File

@@ -1,33 +0,0 @@
"""add passthrough auth to tool
Revision ID: f1ca58b2f2ec
Revises: c7bf5721733e
Create Date: 2024-03-19
"""
from typing import Sequence, Union
from alembic import op
import sqlalchemy as sa
# revision identifiers, used by Alembic.
revision: str = "f1ca58b2f2ec"
down_revision: Union[str, None] = "c7bf5721733e"
branch_labels: Union[str, Sequence[str], None] = None
depends_on: Union[str, Sequence[str], None] = None
def upgrade() -> None:
# Add passthrough_auth column to tool table with default value of False
op.add_column(
"tool",
sa.Column(
"passthrough_auth", sa.Boolean(), nullable=False, server_default=sa.false()
),
)
def downgrade() -> None:
# Remove passthrough_auth column from tool table
op.drop_column("tool", "passthrough_auth")

View File

@@ -1,40 +0,0 @@
"""Add background errors table
Revision ID: f39c5794c10a
Revises: 2cdeff6d8c93
Create Date: 2025-02-12 17:11:14.527876
"""
from alembic import op
import sqlalchemy as sa
# revision identifiers, used by Alembic.
revision = "f39c5794c10a"
down_revision = "2cdeff6d8c93"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.create_table(
"background_error",
sa.Column("id", sa.Integer(), nullable=False),
sa.Column("message", sa.String(), nullable=False),
sa.Column(
"time_created",
sa.DateTime(timezone=True),
server_default=sa.text("now()"),
nullable=False,
),
sa.Column("cc_pair_id", sa.Integer(), nullable=True),
sa.PrimaryKeyConstraint("id"),
sa.ForeignKeyConstraint(
["cc_pair_id"],
["connector_credential_pair.id"],
ondelete="CASCADE",
),
)
def downgrade() -> None:
op.drop_table("background_error")

View File

@@ -1,53 +0,0 @@
"""delete non-search assistants
Revision ID: f5437cc136c5
Revises: eaa3b5593925
Create Date: 2025-02-04 16:17:15.677256
"""
from alembic import op
# revision identifiers, used by Alembic.
revision = "f5437cc136c5"
down_revision = "eaa3b5593925"
branch_labels = None
depends_on = None
def upgrade() -> None:
pass
def downgrade() -> None:
# Fix: split the statements into multiple op.execute() calls
op.execute(
"""
WITH personas_without_search AS (
SELECT p.id
FROM persona p
LEFT JOIN persona__tool pt ON p.id = pt.persona_id
LEFT JOIN tool t ON pt.tool_id = t.id
GROUP BY p.id
HAVING COUNT(CASE WHEN t.in_code_tool_id = 'run_search' THEN 1 END) = 0
)
UPDATE slack_channel_config
SET persona_id = NULL
WHERE is_default = TRUE AND persona_id IN (SELECT id FROM personas_without_search)
"""
)
op.execute(
"""
WITH personas_without_search AS (
SELECT p.id
FROM persona p
LEFT JOIN persona__tool pt ON p.id = pt.persona_id
LEFT JOIN tool t ON pt.tool_id = t.id
GROUP BY p.id
HAVING COUNT(CASE WHEN t.in_code_tool_id = 'run_search' THEN 1 END) = 0
)
DELETE FROM slack_channel_config
WHERE is_default = FALSE AND persona_id IN (SELECT id FROM personas_without_search)
"""
)

View File

@@ -1,41 +0,0 @@
"""Add time_updated to UserGroup and DocumentSet
Revision ID: fec3db967bf7
Revises: 97dbb53fa8c8
Create Date: 2025-01-12 15:49:02.289100
"""
from alembic import op
import sqlalchemy as sa
# revision identifiers, used by Alembic.
revision = "fec3db967bf7"
down_revision = "97dbb53fa8c8"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.add_column(
"document_set",
sa.Column(
"time_last_modified_by_user",
sa.DateTime(timezone=True),
nullable=False,
server_default=sa.func.now(),
),
)
op.add_column(
"user_group",
sa.Column(
"time_last_modified_by_user",
sa.DateTime(timezone=True),
nullable=False,
server_default=sa.func.now(),
),
)
def downgrade() -> None:
op.drop_column("user_group", "time_last_modified_by_user")
op.drop_column("document_set", "time_last_modified_by_user")

View File

@@ -1,42 +0,0 @@
"""lowercase multi-tenant user auth
Revision ID: 34e3630c7f32
Revises: a4f6ee863c47
Create Date: 2025-02-26 15:03:01.211894
"""
from alembic import op
# revision identifiers, used by Alembic.
revision = "34e3630c7f32"
down_revision = "a4f6ee863c47"
branch_labels = None
depends_on = None
def upgrade() -> None:
# 1) Convert all existing rows to lowercase
op.execute(
"""
UPDATE user_tenant_mapping
SET email = LOWER(email)
"""
)
# 2) Add a check constraint so that emails cannot be written in uppercase
op.create_check_constraint(
"ensure_lowercase_email",
"user_tenant_mapping",
"email = LOWER(email)",
schema="public",
)
def downgrade() -> None:
# Drop the check constraint
op.drop_constraint(
"ensure_lowercase_email",
"user_tenant_mapping",
schema="public",
type_="check",
)

536
backend/chatt.txt Normal file
View File

@@ -0,0 +1,536 @@
"{\"user_message_id\": 475, \"reserved_assistant_message_id\": 476}\n"
"{\"sub_question\": \"What\", \"level\": 0, \"level_question_nr\": 1}\n"
"{\"sub_query\": \"ony\", \"level\": 0, \"level_question_nr\": 0, \"query_id\": 0}\n"
"{\"sub_question\": \" is\", \"level\": 0, \"level_question_nr\": 1}\n"
"{\"sub_query\": \"x\", \"level\": 0, \"level_question_nr\": 0, \"query_id\": 0}\n"
"{\"sub_question\": \" On\", \"level\": 0, \"level_question_nr\": 1}\n"
"{\"sub_query\": \" \", \"level\": 0, \"level_question_nr\": 0, \"query_id\": 0}\n"
"{\"sub_question\": \"yx\", \"level\": 0, \"level_question_nr\": 1}\n"
"{\"sub_question\": \" \", \"level\": 0, \"level_question_nr\": 1}\n"
"{\"sub_query\": \"1\", \"level\": 0, \"level_question_nr\": 0, \"query_id\": 0}\n"
"{\"sub_question\": \"1\", \"level\": 0, \"level_question_nr\": 1}\n"
"{\"sub_query\": \" features\", \"level\": 0, \"level_question_nr\": 0, \"query_id\": 0}\n"
"{\"sub_query\": \" and\", \"level\": 0, \"level_question_nr\": 0, \"query_id\": 0}\n"
"{\"sub_question\": \"?\", \"level\": 0, \"level_question_nr\": 1}\n"
"{\"sub_question\": \" \", \"level\": 0, \"level_question_nr\": 1}\n"
"{\"sub_question\": \"\", \"level\": 0, \"level_question_nr\": 2}\n"
"{\"sub_question\": \"What\", \"level\": 0, \"level_question_nr\": 2}\n"
"{\"sub_question\": \" is\", \"level\": 0, \"level_question_nr\": 2}\n"
"{\"sub_query\": \" specifications\", \"level\": 0, \"level_question_nr\": 0, \"query_id\": 0}\n"
"{\"sub_question\": \" On\", \"level\": 0, \"level_question_nr\": 2}\n"
"{\"sub_query\": \" \", \"level\": 0, \"level_question_nr\": 0, \"query_id\": 0}\n"
"{\"sub_query\": \"\", \"level\": 0, \"level_question_nr\": 0, \"query_id\": 1}\n"
"{\"sub_question\": \"yx\", \"level\": 0, \"level_question_nr\": 2}\n"
"{\"sub_question\": \" \", \"level\": 0, \"level_question_nr\": 2}\n"
"{\"sub_question\": \"2\", \"level\": 0, \"level_question_nr\": 2}\n"
"{\"sub_query\": \"ony\", \"level\": 0, \"level_question_nr\": 0, \"query_id\": 1}\n"
"{\"sub_question\": \"?\", \"level\": 0, \"level_question_nr\": 2}\n"
"{\"sub_query\": \"x\", \"level\": 0, \"level_question_nr\": 0, \"query_id\": 1}\n"
"{\"sub_question\": \" \", \"level\": 0, \"level_question_nr\": 2}\n"
"{\"sub_query\": \" \", \"level\": 0, \"level_question_nr\": 0, \"query_id\": 1}\n"
"{\"sub_question\": \"\", \"level\": 0, \"level_question_nr\": 3}\n"
"{\"sub_query\": \"2\", \"level\": 0, \"level_question_nr\": 0, \"query_id\": 1}\n"
"{\"sub_question\": \"What\", \"level\": 0, \"level_question_nr\": 3}\n"
"{\"sub_query\": \" applications\", \"level\": 0, \"level_question_nr\": 0, \"query_id\": 1}\n"
"{\"sub_question\": \" is\", \"level\": 0, \"level_question_nr\": 3}\n"
"{\"sub_query\": \" and\", \"level\": 0, \"level_question_nr\": 0, \"query_id\": 1}\n"
"{\"sub_question\": \" On\", \"level\": 0, \"level_question_nr\": 3}\n"
"{\"sub_query\": \" use\", \"level\": 0, \"level_question_nr\": 0, \"query_id\": 1}\n"
"{\"sub_question\": \"yx\", \"level\": 0, \"level_question_nr\": 3}\n"
"{\"sub_query\": \" cases\", \"level\": 0, \"level_question_nr\": 0, \"query_id\": 1}\n"
"{\"sub_question\": \" \", \"level\": 0, \"level_question_nr\": 3}\n"
"{\"sub_question\": \"3\", \"level\": 0, \"level_question_nr\": 3}\n"
"{\"sub_question\": \"?\", \"level\": 0, \"level_question_nr\": 3}\n"
"{\"sub_question\": \" \", \"level\": 0, \"level_question_nr\": 3}\n"
"{\"sub_question\": \"\", \"level\": 0, \"level_question_nr\": 4}\n"
"{\"sub_question\": \"What\", \"level\": 0, \"level_question_nr\": 4}\n"
"{\"sub_question\": \" is\", \"level\": 0, \"level_question_nr\": 4}\n"
"{\"sub_query\": \" \", \"level\": 0, \"level_question_nr\": 0, \"query_id\": 1}\n"
"{\"sub_question\": \" On\", \"level\": 0, \"level_question_nr\": 4}\n"
"{\"sub_query\": \"\", \"level\": 0, \"level_question_nr\": 0, \"query_id\": 2}\n"
"{\"sub_question\": \"yx\", \"level\": 0, \"level_question_nr\": 4}\n"
"{\"sub_question\": \" \", \"level\": 0, \"level_question_nr\": 4}\n"
"{\"sub_query\": \"ony\", \"level\": 0, \"level_question_nr\": 0, \"query_id\": 2}\n"
"{\"sub_question\": \"4\", \"level\": 0, \"level_question_nr\": 4}\n"
"{\"sub_question\": \"?\", \"level\": 0, \"level_question_nr\": 4}\n"
"{\"sub_query\": \"x\", \"level\": 0, \"level_question_nr\": 0, \"query_id\": 2}\n"
"{\"sub_query\": \" \", \"level\": 0, \"level_question_nr\": 0, \"query_id\": 2}\n"
"{\"sub_question\": \" \", \"level\": 0, \"level_question_nr\": 4}\n"
"{\"sub_question\": \"\", \"level\": 0, \"level_question_nr\": 4}\n"
"{\"sub_query\": \"3\", \"level\": 0, \"level_question_nr\": 0, \"query_id\": 2}\n"
"{\"sub_query\": \" and\", \"level\": 0, \"level_question_nr\": 0, \"query_id\": 2}\n"
"{\"sub_query\": \" \", \"level\": 0, \"level_question_nr\": 0, \"query_id\": 2}\n"
"{\"sub_query\": \"4\", \"level\": 0, \"level_question_nr\": 0, \"query_id\": 2}\n"
"{\"sub_query\": \" comparison\", \"level\": 0, \"level_question_nr\": 0, \"query_id\": 2}\n"
"{\"sub_query\": \" and\", \"level\": 0, \"level_question_nr\": 0, \"query_id\": 2}\n"
"{\"sub_query\": \" differences\", \"level\": 0, \"level_question_nr\": 0, \"query_id\": 2}\n"
"{\"sub_query\": \" \", \"level\": 0, \"level_question_nr\": 0, \"query_id\": 2}\n"
"{\"sub_query\": \"\", \"level\": 0, \"level_question_nr\": 0, \"query_id\": 2}\n"
"{\"sub_query\": \"On\", \"level\": 0, \"level_question_nr\": 3, \"query_id\": 0}\n"
"{\"sub_query\": \"yx\", \"level\": 0, \"level_question_nr\": 3, \"query_id\": 0}\n"
"{\"sub_query\": \"On\", \"level\": 0, \"level_question_nr\": 0, \"query_id\": 0}\n"
"{\"sub_query\": \"yx\", \"level\": 0, \"level_question_nr\": 0, \"query_id\": 0}\n"
"{\"sub_query\": \" \", \"level\": 0, \"level_question_nr\": 3, \"query_id\": 0}\n"
"{\"sub_query\": \"4\", \"level\": 0, \"level_question_nr\": 3, \"query_id\": 0}\n"
"{\"sub_query\": \"On\", \"level\": 0, \"level_question_nr\": 2, \"query_id\": 0}\n"
"{\"sub_query\": \"yx\", \"level\": 0, \"level_question_nr\": 2, \"query_id\": 0}\n"
"{\"sub_query\": \" \", \"level\": 0, \"level_question_nr\": 0, \"query_id\": 0}\n"
"{\"sub_query\": \"1\", \"level\": 0, \"level_question_nr\": 0, \"query_id\": 0}\n"
"{\"sub_query\": \"On\", \"level\": 0, \"level_question_nr\": 1, \"query_id\": 0}\n"
"{\"sub_query\": \" \", \"level\": 0, \"level_question_nr\": 2, \"query_id\": 0}\n"
"{\"sub_query\": \"yx\", \"level\": 0, \"level_question_nr\": 1, \"query_id\": 0}\n"
"{\"sub_query\": \" product\", \"level\": 0, \"level_question_nr\": 0, \"query_id\": 0}\n"
"{\"sub_query\": \"3\", \"level\": 0, \"level_question_nr\": 2, \"query_id\": 0}\n"
"{\"sub_query\": \" information\", \"level\": 0, \"level_question_nr\": 0, \"query_id\": 0}\n"
"{\"sub_query\": \" software\", \"level\": 0, \"level_question_nr\": 3, \"query_id\": 0}\n"
"{\"sub_query\": \" features\", \"level\": 0, \"level_question_nr\": 3, \"query_id\": 0}\n"
"{\"sub_query\": \" \", \"level\": 0, \"level_question_nr\": 1, \"query_id\": 0}\n"
"{\"sub_query\": \" \", \"level\": 0, \"level_question_nr\": 3, \"query_id\": 0}\n"
"{\"sub_query\": \" software\", \"level\": 0, \"level_question_nr\": 2, \"query_id\": 0}\n"
"{\"sub_query\": \"2\", \"level\": 0, \"level_question_nr\": 1, \"query_id\": 0}\n"
"{\"sub_query\": \"\", \"level\": 0, \"level_question_nr\": 3, \"query_id\": 1}\n"
"{\"sub_query\": \" features\", \"level\": 0, \"level_question_nr\": 2, \"query_id\": 0}\n"
"{\"sub_query\": \"On\", \"level\": 0, \"level_question_nr\": 3, \"query_id\": 1}\n"
"{\"sub_query\": \" \", \"level\": 0, \"level_question_nr\": 0, \"query_id\": 0}\n"
"{\"sub_query\": \"\", \"level\": 0, \"level_question_nr\": 0, \"query_id\": 1}\n"
"{\"sub_query\": \"On\", \"level\": 0, \"level_question_nr\": 0, \"query_id\": 1}\n"
"{\"sub_query\": \"yx\", \"level\": 0, \"level_question_nr\": 3, \"query_id\": 1}\n"
"{\"sub_query\": \" \", \"level\": 0, \"level_question_nr\": 3, \"query_id\": 1}\n"
"{\"sub_query\": \"yx\", \"level\": 0, \"level_question_nr\": 0, \"query_id\": 1}\n"
"{\"sub_query\": \" \", \"level\": 0, \"level_question_nr\": 0, \"query_id\": 1}\n"
"{\"sub_query\": \" software\", \"level\": 0, \"level_question_nr\": 1, \"query_id\": 0}\n"
"{\"sub_query\": \" features\", \"level\": 0, \"level_question_nr\": 1, \"query_id\": 0}\n"
"{\"sub_query\": \"4\", \"level\": 0, \"level_question_nr\": 3, \"query_id\": 1}\n"
"{\"sub_query\": \" applications\", \"level\": 0, \"level_question_nr\": 3, \"query_id\": 1}\n"
"{\"sub_query\": \" \", \"level\": 0, \"level_question_nr\": 1, \"query_id\": 0}\n"
"{\"sub_query\": \"1\", \"level\": 0, \"level_question_nr\": 0, \"query_id\": 1}\n"
"{\"sub_query\": \"\", \"level\": 0, \"level_question_nr\": 1, \"query_id\": 1}\n"
"{\"sub_query\": \" features\", \"level\": 0, \"level_question_nr\": 0, \"query_id\": 1}\n"
"{\"sub_query\": \"On\", \"level\": 0, \"level_question_nr\": 1, \"query_id\": 1}\n"
"{\"sub_query\": \" in\", \"level\": 0, \"level_question_nr\": 3, \"query_id\": 1}\n"
"{\"sub_query\": \" industry\", \"level\": 0, \"level_question_nr\": 3, \"query_id\": 1}\n"
"{\"sub_query\": \" \", \"level\": 0, \"level_question_nr\": 2, \"query_id\": 0}\n"
"{\"sub_query\": \"\", \"level\": 0, \"level_question_nr\": 2, \"query_id\": 1}\n"
"{\"sub_query\": \"yx\", \"level\": 0, \"level_question_nr\": 1, \"query_id\": 1}\n"
"{\"sub_query\": \"On\", \"level\": 0, \"level_question_nr\": 2, \"query_id\": 1}\n"
"{\"sub_query\": \" \", \"level\": 0, \"level_question_nr\": 1, \"query_id\": 1}\n"
"{\"sub_query\": \" and\", \"level\": 0, \"level_question_nr\": 0, \"query_id\": 1}\n"
"{\"sub_query\": \"yx\", \"level\": 0, \"level_question_nr\": 2, \"query_id\": 1}\n"
"{\"sub_query\": \" specifications\", \"level\": 0, \"level_question_nr\": 0, \"query_id\": 1}\n"
"{\"sub_query\": \" \", \"level\": 0, \"level_question_nr\": 2, \"query_id\": 1}\n"
"{\"sub_query\": \"2\", \"level\": 0, \"level_question_nr\": 1, \"query_id\": 1}\n"
"{\"sub_query\": \" applications\", \"level\": 0, \"level_question_nr\": 1, \"query_id\": 1}\n"
"{\"sub_query\": \" \", \"level\": 0, \"level_question_nr\": 3, \"query_id\": 1}\n"
"{\"sub_query\": \" \", \"level\": 0, \"level_question_nr\": 0, \"query_id\": 1}\n"
"{\"sub_query\": \"\", \"level\": 0, \"level_question_nr\": 3, \"query_id\": 2}\n"
"{\"sub_query\": \"\", \"level\": 0, \"level_question_nr\": 0, \"query_id\": 2}\n"
"{\"sub_query\": \"On\", \"level\": 0, \"level_question_nr\": 3, \"query_id\": 2}\n"
"{\"sub_query\": \"On\", \"level\": 0, \"level_question_nr\": 0, \"query_id\": 2}\n"
"{\"sub_query\": \"3\", \"level\": 0, \"level_question_nr\": 2, \"query_id\": 1}\n"
"{\"sub_query\": \"yx\", \"level\": 0, \"level_question_nr\": 0, \"query_id\": 2}\n"
"{\"sub_query\": \" applications\", \"level\": 0, \"level_question_nr\": 2, \"query_id\": 1}\n"
"{\"sub_query\": \" \", \"level\": 0, \"level_question_nr\": 0, \"query_id\": 2}\n"
"{\"sub_query\": \"yx\", \"level\": 0, \"level_question_nr\": 3, \"query_id\": 2}\n"
"{\"sub_query\": \" in\", \"level\": 0, \"level_question_nr\": 1, \"query_id\": 1}\n"
"{\"sub_query\": \" \", \"level\": 0, \"level_question_nr\": 3, \"query_id\": 2}\n"
"{\"sub_query\": \" industry\", \"level\": 0, \"level_question_nr\": 1, \"query_id\": 1}\n"
"{\"sub_query\": \"1\", \"level\": 0, \"level_question_nr\": 0, \"query_id\": 2}\n"
"{\"sub_query\": \" applications\", \"level\": 0, \"level_question_nr\": 0, \"query_id\": 2}\n"
"{\"sub_query\": \" \", \"level\": 0, \"level_question_nr\": 1, \"query_id\": 1}\n"
"{\"sub_query\": \"\", \"level\": 0, \"level_question_nr\": 1, \"query_id\": 2}\n"
"{\"sub_query\": \"On\", \"level\": 0, \"level_question_nr\": 1, \"query_id\": 2}\n"
"{\"sub_query\": \"4\", \"level\": 0, \"level_question_nr\": 3, \"query_id\": 2}\n"
"{\"sub_query\": \" comparison\", \"level\": 0, \"level_question_nr\": 3, \"query_id\": 2}\n"
"{\"sub_query\": \" with\", \"level\": 0, \"level_question_nr\": 3, \"query_id\": 2}\n"
"{\"sub_query\": \" and\", \"level\": 0, \"level_question_nr\": 0, \"query_id\": 2}\n"
"{\"sub_query\": \" previous\", \"level\": 0, \"level_question_nr\": 3, \"query_id\": 2}\n"
"{\"sub_query\": \" use\", \"level\": 0, \"level_question_nr\": 0, \"query_id\": 2}\n"
"{\"sub_query\": \" versions\", \"level\": 0, \"level_question_nr\": 3, \"query_id\": 2}\n"
"{\"sub_query\": \" in\", \"level\": 0, \"level_question_nr\": 2, \"query_id\": 1}\n"
"{\"sub_query\": \" industry\", \"level\": 0, \"level_question_nr\": 2, \"query_id\": 1}\n"
"{\"sub_query\": \" \", \"level\": 0, \"level_question_nr\": 3, \"query_id\": 2}\n"
"{\"sub_query\": \"\", \"level\": 0, \"level_question_nr\": 3, \"query_id\": 2}\n"
"{\"sub_query\": \"yx\", \"level\": 0, \"level_question_nr\": 1, \"query_id\": 2}\n"
"{\"sub_query\": \" \", \"level\": 0, \"level_question_nr\": 2, \"query_id\": 1}\n"
"{\"sub_query\": \"\", \"level\": 0, \"level_question_nr\": 2, \"query_id\": 2}\n"
"{\"sub_query\": \" \", \"level\": 0, \"level_question_nr\": 1, \"query_id\": 2}\n"
"{\"sub_query\": \"On\", \"level\": 0, \"level_question_nr\": 2, \"query_id\": 2}\n"
"{\"sub_query\": \"yx\", \"level\": 0, \"level_question_nr\": 2, \"query_id\": 2}\n"
"{\"sub_query\": \" \", \"level\": 0, \"level_question_nr\": 2, \"query_id\": 2}\n"
"{\"sub_query\": \"3\", \"level\": 0, \"level_question_nr\": 2, \"query_id\": 2}\n"
"{\"sub_query\": \" comparison\", \"level\": 0, \"level_question_nr\": 2, \"query_id\": 2}\n"
"{\"sub_query\": \"2\", \"level\": 0, \"level_question_nr\": 1, \"query_id\": 2}\n"
"{\"sub_query\": \" comparison\", \"level\": 0, \"level_question_nr\": 1, \"query_id\": 2}\n"
"{\"sub_query\": \" with\", \"level\": 0, \"level_question_nr\": 2, \"query_id\": 2}\n"
"{\"sub_query\": \" cases\", \"level\": 0, \"level_question_nr\": 0, \"query_id\": 2}\n"
"{\"sub_query\": \" previous\", \"level\": 0, \"level_question_nr\": 2, \"query_id\": 2}\n"
"{\"sub_query\": \" \", \"level\": 0, \"level_question_nr\": 0, \"query_id\": 2}\n"
"{\"sub_query\": \"\", \"level\": 0, \"level_question_nr\": 0, \"query_id\": 2}\n"
"{\"sub_query\": \" with\", \"level\": 0, \"level_question_nr\": 1, \"query_id\": 2}\n"
"{\"sub_query\": \" other\", \"level\": 0, \"level_question_nr\": 1, \"query_id\": 2}\n"
"{\"sub_query\": \" software\", \"level\": 0, \"level_question_nr\": 1, \"query_id\": 2}\n"
"{\"sub_query\": \"\", \"level\": 0, \"level_question_nr\": 1, \"query_id\": 2}\n"
"{\"sub_query\": \" versions\", \"level\": 0, \"level_question_nr\": 2, \"query_id\": 2}\n"
"{\"sub_query\": \" \", \"level\": 0, \"level_question_nr\": 2, \"query_id\": 2}\n"
"{\"sub_query\": \"\", \"level\": 0, \"level_question_nr\": 2, \"query_id\": 2}\n"
"{\"top_documents\": [], \"rephrased_query\": \"What is Onyx 4?\", \"predicted_flow\": \"question-answer\", \"predicted_search\": \"keyword\", \"applied_source_filters\": null, \"applied_time_cutoff\": null, \"recency_bias_multiplier\": 0.5}\n"
"{\"llm_selected_doc_indices\": []}\n"
"{\"final_context_docs\": []}\n"
"{\"answer_piece\": \"I\", \"level\": 0, \"level_question_nr\": 3, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" don't\", \"level\": 0, \"level_question_nr\": 3, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \"On\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" know\", \"level\": 0, \"level_question_nr\": 3, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \"yx\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \".\", \"level\": 0, \"level_question_nr\": 3, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" \", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \"1\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \",\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" formerly\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" known\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" as\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" D\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \"answer\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \",\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" is\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" an\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" AI\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" Assistant\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" that\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" connects\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" to\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" a\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" company's\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" documents\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \",\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" applications\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \",\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" and\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" personnel\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \".\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" It\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" provides\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" a\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" chat\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" interface\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" and\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" can\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" integrate\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" with\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" any\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" large\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" language\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" model\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" (\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \"LL\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \"M\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \")\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"top_documents\": [], \"rephrased_query\": \"What is Onyx 2?\", \"predicted_flow\": \"question-answer\", \"predicted_search\": \"keyword\", \"applied_source_filters\": null, \"applied_time_cutoff\": null, \"recency_bias_multiplier\": 0.5}\n"
"{\"llm_selected_doc_indices\": []}\n"
"{\"final_context_docs\": []}\n"
"{\"answer_piece\": \" of\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" choice\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \".\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" On\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \"yx\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" is\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" designed\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" to\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" be\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" modular\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" and\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" easily\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" extens\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \"ible\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \",\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" allowing\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" for\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" deployment\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" on\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" various\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" platforms\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \",\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" including\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" laptops\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \",\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" on\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \"-prem\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \"ise\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \",\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" or\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" cloud\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" environments\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \".\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" It\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" ensures\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" that\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" user\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" data\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" and\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" chats\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" remain\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \"I\", \"level\": 0, \"level_question_nr\": 1, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" under\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" don't\", \"level\": 0, \"level_question_nr\": 1, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" the\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" user's\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" know\", \"level\": 0, \"level_question_nr\": 1, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \".\", \"level\": 0, \"level_question_nr\": 1, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" control\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \",\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" as\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" the\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" deployment\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" is\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" owned\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" by\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" the\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" user\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \".\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" On\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \"yx\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" is\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" MIT\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" licensed\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" and\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" comes\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" ready\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" for\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" production\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" use\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \",\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" featuring\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" user\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" authentication\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \",\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" role\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" management\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \",\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" chat\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" persistence\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \",\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" and\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" a\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" user\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" interface\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" for\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" configuring\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" AI\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" Assist\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \"ants\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" and\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" their\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" prompts\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \".\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" Additionally\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \",\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" On\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \"yx\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" serves\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" as\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" a\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" unified\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" search\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" tool\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" across\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" common\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" workplace\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" applications\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" like\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" Slack\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \",\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" Google\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" Drive\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \",\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" and\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" Con\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \"fluence\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \",\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" enabling\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" it\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" to\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" act\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" as\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" a\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" subject\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" matter\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" expert\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" for\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" teams\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" by\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" combining\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" L\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \"LM\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \"s\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" with\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" team\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \"-specific\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" knowledge\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" [[1]]()\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"top_documents\": [], \"rephrased_query\": \"What is Onyx 3?\", \"predicted_flow\": \"question-answer\", \"predicted_search\": \"keyword\", \"applied_source_filters\": null, \"applied_time_cutoff\": null, \"recency_bias_multiplier\": 0.5}\n"
"{\"llm_selected_doc_indices\": []}\n"
"{\"final_context_docs\": []}\n"
"{\"answer_piece\": \"I\", \"level\": 0, \"level_question_nr\": 2, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" don't\", \"level\": 0, \"level_question_nr\": 2, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \" know\", \"level\": 0, \"level_question_nr\": 2, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"answer_piece\": \".\", \"level\": 0, \"level_question_nr\": 2, \"answer_type\": \"agent_sub_answer\"}\n"
"{\"top_documents\": [{\"document_id\": \"https://docs.onyx.app/introduction\", \"chunk_ind\": 0, \"semantic_identifier\": \"Introduction - Onyx Documentation\", \"link\": \"https://docs.onyx.app/introduction\", \"blurb\": \"Onyx Documentation home page\\nSearch...\\nNavigation\\nWelcome to Onyx\\nIntroduction\\nWelcome to Onyx\\nIntroduction\\nOnyx Overview\\n\\nWhat is Onyx\\nOnyx (Formerly Danswer) is the AI Assistant connected to your companys docs, apps, and people. Onyx provides a Chat interface and plugs into any LLM of your choice. Onyx can be deployed anywhere and for any scale - on a laptop, on-premise, or to cloud. Since you own the deployment, your user data and chats are fully in your own control. Onyx is MIT licensed and designed to be modular and easily extensible.\", \"source_type\": \"web\", \"boost\": 0, \"hidden\": false, \"metadata\": {}, \"score\": 0.6275177643886491, \"is_relevant\": null, \"relevance_explanation\": null, \"match_highlights\": [\"\", \"such as A customer wants feature X, is this already supported? or Wheres the pull request for feature Y?\\n<hi>Onyx</hi> can also be plugged into existing tools like Slack to get answers and AI chats directly in Slack.\\n\\nDemo\\n\\nMain <hi>Features</hi> \\n- Chat UI with the ability to select documents to chat with.\\n- Create custom AI Assistants\", \"\"], \"updated_at\": null, \"primary_owners\": null, \"secondary_owners\": null, \"is_internet\": false, \"db_doc_id\": 35923}], \"rephrased_query\": \"what is onyx 1, 2, 3, 4\", \"predicted_flow\": \"question-answer\", \"predicted_search\": \"keyword\", \"applied_source_filters\": null, \"applied_time_cutoff\": null, \"recency_bias_multiplier\": 0.5}\n"
"{\"llm_selected_doc_indices\": []}\n"
"{\"final_context_docs\": [{\"document_id\": \"https://docs.onyx.app/introduction\", \"content\": \"Onyx Documentation home page\\nSearch...\\nNavigation\\nWelcome to Onyx\\nIntroduction\\nWelcome to Onyx\\nIntroduction\\nOnyx Overview\\n\\nWhat is Onyx\\nOnyx (Formerly Danswer) is the AI Assistant connected to your companys docs, apps, and people. Onyx provides a Chat interface and plugs into any LLM of your choice. Onyx can be deployed anywhere and for any scale - on a laptop, on-premise, or to cloud. Since you own the deployment, your user data and chats are fully in your own control. Onyx is MIT licensed and designed to be modular and easily extensible. The system also comes fully ready for production usage with user authentication, role management (admin/basic users), chat persistence, and a UI for configuring Personas (AI Assistants) and their Prompts.\\nOnyx also serves as a Unified Search across all common workplace tools such as Slack, Google Drive, Confluence, etc. By combining LLMs and team specific knowledge, Onyx becomes a subject matter expert for the team. Its like ChatGPT if it had access to your teams unique knowledge! It enables questions such as A customer wants feature X, is this already supported? or Wheres the pull request for feature Y?\\nOnyx can also be plugged into existing tools like Slack to get answers and AI chats directly in Slack.\\n\\nDemo\\n\\nMain Features \\n- Chat UI with the ability to select documents to chat with.\\n- Create custom AI Assistants with different prompts and backing knowledge sets.\\n- Connect Onyx with LLM of your choice (self-host for a fully airgapped solution).\\n- Document Search + AI Answers for natural language queries.\\n- Connectors to all common workplace tools like Google Drive, Confluence, Slack, etc.\\n- Slack integration to get answers and search results directly in Slack.\\n\\nUpcoming\\n- Chat/Prompt sharing with specific teammates and user groups.\\n- Multi-modal model support, chat with images, video etc.\\n- Choosing between LLMs and parameters during chat session.\\n- Tool calling and agent configurations options.\\n- Organizational understanding and ability to locate and suggest experts from your team.\\n\\nOther Noteable Benefits of Onyx\\n- User Authentication with document level access management.\\n- Best in class Hybrid Search across all sources (BM-25 + prefix aware embedding models).\\n- Admin Dashboard to configure connectors, document-sets, access, etc.\\n- Custom deep learning models + learn from user feedback.\\n- Easy deployment and ability to host Onyx anywhere of your choosing.\\nQuickstart\", \"blurb\": \"Onyx Documentation home page\\nSearch...\\nNavigation\\nWelcome to Onyx\\nIntroduction\\nWelcome to Onyx\\nIntroduction\\nOnyx Overview\\n\\nWhat is Onyx\\nOnyx (Formerly Danswer) is the AI Assistant connected to your companys docs, apps, and people. Onyx provides a Chat interface and plugs into any LLM of your choice. Onyx can be deployed anywhere and for any scale - on a laptop, on-premise, or to cloud. Since you own the deployment, your user data and chats are fully in your own control. Onyx is MIT licensed and designed to be modular and easily extensible.\", \"semantic_identifier\": \"Introduction - Onyx Documentation\", \"source_type\": \"web\", \"metadata\": {}, \"updated_at\": null, \"link\": \"https://docs.onyx.app/introduction\", \"source_links\": {\"0\": \"https://docs.onyx.app/introduction\"}, \"match_highlights\": [\"\", \"such as A customer wants feature X, is this already supported? or Wheres the pull request for feature Y?\\n<hi>Onyx</hi> can also be plugged into existing tools like Slack to get answers and AI chats directly in Slack.\\n\\nDemo\\n\\nMain <hi>Features</hi> \\n- Chat UI with the ability to select documents to chat with.\\n- Create custom AI Assistants\", \"\"]}]}\n"
"{\"answer_piece\": \"I\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" cannot\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" reliably\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" answer\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" the\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" question\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" about\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" On\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \"yx\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" \", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \"2\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \",\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" \", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \"3\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \",\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" and\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" \", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \"4\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \",\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" as\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" the\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" provided\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" information\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" only\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" describes\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" On\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \"yx\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" \", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \"1\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \",\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" which\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" is\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" an\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" AI\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" Assistant\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" formerly\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" known\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" as\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" D\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \"answer\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \".\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" On\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \"yx\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" \", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \"1\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" connects\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" to\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" a\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" company's\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" documents\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \",\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" applications\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \",\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" and\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" personnel\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \",\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" providing\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" a\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" chat\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" interface\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" and\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" integration\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" with\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" any\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" large\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" language\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" model\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" (\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \"LL\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \"M\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \")\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" of\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" choice\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \".\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" It\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" is\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" designed\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" to\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" be\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" modular\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \",\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" easily\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" extens\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \"ible\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \",\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" and\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" can\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" be\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" deployed\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" on\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" various\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" platforms\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" while\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" ensuring\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" user\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" data\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" control\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \".\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" It\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" also\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" serves\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" as\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" a\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" unified\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" search\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" tool\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" across\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" common\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" workplace\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" applications\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" like\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" Slack\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \",\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" Google\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" Drive\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \",\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" and\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" Con\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \"fluence\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \",\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" acting\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" as\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" a\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" subject\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" matter\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" expert\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" for\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" teams\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" [[1]]()\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \"{{1}}\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \"There\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" is\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" no\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" information\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" available\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" regarding\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" On\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \"yx\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" \", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \"2\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \",\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" \", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \"3\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \",\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" or\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" \", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \"4\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \",\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" so\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" I\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" cannot\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" provide\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" details\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" about\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \" them\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"answer_piece\": \".\", \"level\": 0, \"level_question_nr\": 0, \"answer_type\": \"agent_level_answer\"}\n"
"{\"citations\": []}\n"
"{\"message_id\": 476, \"parent_message\": 475, \"latest_child_message\": null, \"message\": \"I cannot reliably answer the question about Onyx 2, 3, and 4, as the provided information only describes Onyx 1, which is an AI Assistant formerly known as Danswer. Onyx 1 connects to a company's documents, applications, and personnel, providing a chat interface and integration with any large language model (LLM) of choice. It is designed to be modular, easily extensible, and can be deployed on various platforms while ensuring user data control. It also serves as a unified search tool across common workplace applications like Slack, Google Drive, and Confluence, acting as a subject matter expert for teams [[1]](){{1}}There is no information available regarding Onyx 2, 3, or 4, so I cannot provide details about them.\", \"rephrased_query\": \"what is onyx 1, 2, 3, 4\", \"context_docs\": {\"top_documents\": [{\"document_id\": \"https://docs.onyx.app/introduction\", \"chunk_ind\": 0, \"semantic_identifier\": \"Introduction - Onyx Documentation\", \"link\": \"https://docs.onyx.app/introduction\", \"blurb\": \"Onyx Documentation home page\\nSearch...\\nNavigation\\nWelcome to Onyx\\nIntroduction\\nWelcome to Onyx\\nIntroduction\\nOnyx Overview\\n\\nWhat is Onyx\\nOnyx (Formerly Danswer) is the AI Assistant connected to your companys docs, apps, and people. Onyx provides a Chat interface and plugs into any LLM of your choice. Onyx can be deployed anywhere and for any scale - on a laptop, on-premise, or to cloud. Since you own the deployment, your user data and chats are fully in your own control. Onyx is MIT licensed and designed to be modular and easily extensible.\", \"source_type\": \"web\", \"boost\": 0, \"hidden\": false, \"metadata\": {}, \"score\": 0.6275177643886491, \"is_relevant\": null, \"relevance_explanation\": null, \"match_highlights\": [\"\", \"such as A customer wants feature X, is this already supported? or Wheres the pull request for feature Y?\\n<hi>Onyx</hi> can also be plugged into existing tools like Slack to get answers and AI chats directly in Slack.\\n\\nDemo\\n\\nMain <hi>Features</hi> \\n- Chat UI with the ability to select documents to chat with.\\n- Create custom AI Assistants\", \"\"], \"updated_at\": null, \"primary_owners\": null, \"secondary_owners\": null, \"is_internet\": false, \"db_doc_id\": 35923}]}, \"message_type\": \"assistant\", \"time_sent\": \"2025-01-12T05:37:18.318251+00:00\", \"overridden_model\": \"gpt-4o\", \"alternate_assistant_id\": 0, \"chat_session_id\": \"40f91916-7419-48d1-9681-5882b0869d88\", \"citations\": {}, \"sub_questions\": [], \"files\": [], \"tool_call\": null}\n"

View File

@@ -5,9 +5,11 @@ from onyx.background.celery.apps.primary import celery_app
from onyx.background.task_utils import build_celery_task_wrapper
from onyx.configs.app_configs import JOB_TIMEOUT
from onyx.db.chat import delete_chat_sessions_older_than
from onyx.db.engine import get_session_with_current_tenant
from onyx.db.engine import get_session_with_tenant
from onyx.server.settings.store import load_settings
from onyx.utils.logger import setup_logger
from shared_configs.configs import MULTI_TENANT
from shared_configs.contextvars import CURRENT_TENANT_ID_CONTEXTVAR
logger = setup_logger()
@@ -16,8 +18,10 @@ logger = setup_logger()
@build_celery_task_wrapper(name_chat_ttl_task)
@celery_app.task(soft_time_limit=JOB_TIMEOUT)
def perform_ttl_management_task(retention_limit_days: int, *, tenant_id: str) -> None:
with get_session_with_current_tenant() as db_session:
def perform_ttl_management_task(
retention_limit_days: int, *, tenant_id: str | None
) -> None:
with get_session_with_tenant(tenant_id) as db_session:
delete_chat_sessions_older_than(retention_limit_days, db_session)
@@ -28,32 +32,35 @@ def perform_ttl_management_task(retention_limit_days: int, *, tenant_id: str) ->
@celery_app.task(
name="check_ttl_management_task",
ignore_result=True,
soft_time_limit=JOB_TIMEOUT,
)
def check_ttl_management_task(*, tenant_id: str) -> None:
def check_ttl_management_task(*, tenant_id: str | None) -> None:
"""Runs periodically to check if any ttl tasks should be run and adds them
to the queue"""
token = None
if MULTI_TENANT and tenant_id is not None:
token = CURRENT_TENANT_ID_CONTEXTVAR.set(tenant_id)
settings = load_settings()
retention_limit_days = settings.maximum_chat_retention_days
with get_session_with_current_tenant() as db_session:
with get_session_with_tenant(tenant_id) as db_session:
if should_perform_chat_ttl_check(retention_limit_days, db_session):
perform_ttl_management_task.apply_async(
kwargs=dict(
retention_limit_days=retention_limit_days, tenant_id=tenant_id
),
)
if token is not None:
CURRENT_TENANT_ID_CONTEXTVAR.reset(token)
@celery_app.task(
name="autogenerate_usage_report_task",
ignore_result=True,
soft_time_limit=JOB_TIMEOUT,
)
def autogenerate_usage_report_task(*, tenant_id: str) -> None:
def autogenerate_usage_report_task(*, tenant_id: str | None) -> None:
"""This generates usage report under the /admin/generate-usage/report endpoint"""
with get_session_with_current_tenant() as db_session:
with get_session_with_tenant(tenant_id) as db_session:
create_new_usage_report(
db_session=db_session,
user_id=None,

View File

@@ -2,79 +2,23 @@ from datetime import timedelta
from typing import Any
from onyx.background.celery.tasks.beat_schedule import (
beat_cloud_tasks as base_beat_system_tasks,
tasks_to_schedule as base_tasks_to_schedule,
)
from onyx.background.celery.tasks.beat_schedule import BEAT_EXPIRES_DEFAULT
from onyx.background.celery.tasks.beat_schedule import (
beat_task_templates as base_beat_task_templates,
)
from onyx.background.celery.tasks.beat_schedule import generate_cloud_tasks
from onyx.background.celery.tasks.beat_schedule import (
get_tasks_to_schedule as base_get_tasks_to_schedule,
)
from onyx.configs.constants import OnyxCeleryPriority
from onyx.configs.constants import OnyxCeleryTask
from shared_configs.configs import MULTI_TENANT
ee_beat_system_tasks: list[dict] = []
ee_beat_task_templates: list[dict] = []
ee_beat_task_templates.extend(
[
{
"name": "autogenerate-usage-report",
"task": OnyxCeleryTask.AUTOGENERATE_USAGE_REPORT_TASK,
"schedule": timedelta(days=30),
"options": {
"priority": OnyxCeleryPriority.MEDIUM,
"expires": BEAT_EXPIRES_DEFAULT,
},
},
{
"name": "check-ttl-management",
"task": OnyxCeleryTask.CHECK_TTL_MANAGEMENT_TASK,
"schedule": timedelta(hours=1),
"options": {
"priority": OnyxCeleryPriority.MEDIUM,
"expires": BEAT_EXPIRES_DEFAULT,
},
},
]
)
ee_tasks_to_schedule: list[dict] = []
if not MULTI_TENANT:
ee_tasks_to_schedule = [
{
"name": "autogenerate-usage-report",
"task": OnyxCeleryTask.AUTOGENERATE_USAGE_REPORT_TASK,
"schedule": timedelta(days=30), # TODO: change this to config flag
"options": {
"priority": OnyxCeleryPriority.MEDIUM,
"expires": BEAT_EXPIRES_DEFAULT,
},
},
{
"name": "check-ttl-management",
"task": OnyxCeleryTask.CHECK_TTL_MANAGEMENT_TASK,
"schedule": timedelta(hours=1),
"options": {
"priority": OnyxCeleryPriority.MEDIUM,
"expires": BEAT_EXPIRES_DEFAULT,
},
},
]
def get_cloud_tasks_to_schedule(beat_multiplier: float) -> list[dict[str, Any]]:
beat_system_tasks = ee_beat_system_tasks + base_beat_system_tasks
beat_task_templates = ee_beat_task_templates + base_beat_task_templates
cloud_tasks = generate_cloud_tasks(
beat_system_tasks, beat_task_templates, beat_multiplier
)
return cloud_tasks
ee_tasks_to_schedule = [
{
"name": "autogenerate_usage_report",
"task": OnyxCeleryTask.AUTOGENERATE_USAGE_REPORT_TASK,
"schedule": timedelta(days=30), # TODO: change this to config flag
},
{
"name": "check-ttl-management",
"task": OnyxCeleryTask.CHECK_TTL_MANAGEMENT_TASK,
"schedule": timedelta(hours=1),
},
]
def get_tasks_to_schedule() -> list[dict[str, Any]]:
return ee_tasks_to_schedule + base_get_tasks_to_schedule()
return ee_tasks_to_schedule + base_tasks_to_schedule

View File

@@ -8,9 +8,6 @@ from ee.onyx.db.user_group import fetch_user_group
from ee.onyx.db.user_group import mark_user_group_as_synced
from ee.onyx.db.user_group import prepare_user_group_for_deletion
from onyx.background.celery.apps.app_base import task_logger
from onyx.db.enums import SyncStatus
from onyx.db.enums import SyncType
from onyx.db.sync_record import update_sync_record_status
from onyx.redis.redis_usergroup import RedisUserGroup
from onyx.utils.logger import setup_logger
@@ -18,7 +15,7 @@ logger = setup_logger()
def monitor_usergroup_taskset(
tenant_id: str, key_bytes: bytes, r: Redis, db_session: Session
tenant_id: str | None, key_bytes: bytes, r: Redis, db_session: Session
) -> None:
"""This function is likely to move in the worker refactor happening next."""
fence_key = key_bytes.decode("utf-8")
@@ -46,59 +43,24 @@ def monitor_usergroup_taskset(
f"User group sync progress: usergroup_id={usergroup_id} remaining={count} initial={initial_count}"
)
if count > 0:
update_sync_record_status(
db_session=db_session,
entity_id=usergroup_id,
sync_type=SyncType.USER_GROUP,
sync_status=SyncStatus.IN_PROGRESS,
num_docs_synced=count,
)
return
user_group = fetch_user_group(db_session=db_session, user_group_id=usergroup_id)
if user_group:
usergroup_name = user_group.name
try:
if user_group.is_up_for_deletion:
# this prepare should have been run when the deletion was scheduled,
# but run it again to be sure we're ready to go
mark_user_group_as_synced(db_session, user_group)
prepare_user_group_for_deletion(db_session, usergroup_id)
delete_user_group(db_session=db_session, user_group=user_group)
update_sync_record_status(
db_session=db_session,
entity_id=usergroup_id,
sync_type=SyncType.USER_GROUP,
sync_status=SyncStatus.SUCCESS,
num_docs_synced=initial_count,
)
task_logger.info(
f"Deleted usergroup: name={usergroup_name} id={usergroup_id}"
)
else:
mark_user_group_as_synced(db_session=db_session, user_group=user_group)
update_sync_record_status(
db_session=db_session,
entity_id=usergroup_id,
sync_type=SyncType.USER_GROUP,
sync_status=SyncStatus.SUCCESS,
num_docs_synced=initial_count,
)
task_logger.info(
f"Synced usergroup. name={usergroup_name} id={usergroup_id}"
)
except Exception as e:
update_sync_record_status(
db_session=db_session,
entity_id=usergroup_id,
sync_type=SyncType.USER_GROUP,
sync_status=SyncStatus.FAILED,
num_docs_synced=initial_count,
if user_group.is_up_for_deletion:
# this prepare should have been run when the deletion was scheduled,
# but run it again to be sure we're ready to go
mark_user_group_as_synced(db_session, user_group)
prepare_user_group_for_deletion(db_session, usergroup_id)
delete_user_group(db_session=db_session, user_group=user_group)
task_logger.info(
f"Deleted usergroup: name={usergroup_name} id={usergroup_id}"
)
else:
mark_user_group_as_synced(db_session=db_session, user_group=user_group)
task_logger.info(
f"Synced usergroup. name={usergroup_name} id={usergroup_id}"
)
raise e
rug.reset()

View File

@@ -4,20 +4,6 @@ import os
# Applicable for OIDC Auth
OPENID_CONFIG_URL = os.environ.get("OPENID_CONFIG_URL", "")
# Applicable for OIDC Auth, allows you to override the scopes that
# are requested from the OIDC provider. Currently used when passing
# over access tokens to tool calls and the tool needs more scopes
OIDC_SCOPE_OVERRIDE: list[str] | None = None
_OIDC_SCOPE_OVERRIDE = os.environ.get("OIDC_SCOPE_OVERRIDE")
if _OIDC_SCOPE_OVERRIDE:
try:
OIDC_SCOPE_OVERRIDE = [
scope.strip() for scope in _OIDC_SCOPE_OVERRIDE.split(",")
]
except Exception:
pass
# Applicable for SAML Auth
SAML_CONF_DIR = os.environ.get("SAML_CONF_DIR") or "/app/ee/onyx/configs/saml_config"
@@ -77,5 +63,3 @@ POSTHOG_HOST = os.environ.get("POSTHOG_HOST") or "https://us.i.posthog.com"
HUBSPOT_TRACKING_URL = os.environ.get("HUBSPOT_TRACKING_URL")
ANONYMOUS_USER_COOKIE_NAME = "onyx_anonymous_user"
GATED_TENANTS_KEY = "gated_tenants"

View File

@@ -4,7 +4,6 @@ from sqlalchemy.orm import Session
from onyx.configs.constants import DocumentSource
from onyx.db.connector_credential_pair import get_connector_credential_pair
from onyx.db.enums import AccessType
from onyx.db.enums import ConnectorCredentialPairStatus
from onyx.db.models import Connector
from onyx.db.models import ConnectorCredentialPair
from onyx.db.models import UserGroup__ConnectorCredentialPair
@@ -36,11 +35,10 @@ def _delete_connector_credential_pair_user_groups_relationship__no_commit(
def get_cc_pairs_by_source(
db_session: Session,
source_type: DocumentSource,
access_type: AccessType | None = None,
status: ConnectorCredentialPairStatus | None = None,
only_sync: bool,
) -> list[ConnectorCredentialPair]:
"""
Get all cc_pairs for a given source type with optional filtering by access_type and status
Get all cc_pairs for a given source type (and optionally only sync)
result is sorted by cc_pair id
"""
query = (
@@ -50,11 +48,8 @@ def get_cc_pairs_by_source(
.order_by(ConnectorCredentialPair.id)
)
if access_type is not None:
query = query.filter(ConnectorCredentialPair.access_type == access_type)
if status is not None:
query = query.filter(ConnectorCredentialPair.status == status)
if only_sync:
query = query.filter(ConnectorCredentialPair.access_type == AccessType.SYNC)
cc_pairs = query.all()
return cc_pairs

View File

@@ -5,7 +5,7 @@ from sqlalchemy import select
from sqlalchemy.orm import Session
from onyx.access.models import ExternalAccess
from onyx.access.utils import build_ext_group_name_for_onyx
from onyx.access.utils import prefix_group_w_source
from onyx.configs.constants import DocumentSource
from onyx.db.models import Document as DbDocument
@@ -25,7 +25,7 @@ def upsert_document_external_perms__no_commit(
).first()
prefixed_external_groups = [
build_ext_group_name_for_onyx(
prefix_group_w_source(
ext_group_name=group_id,
source=source_type,
)
@@ -66,7 +66,7 @@ def upsert_document_external_perms(
).first()
prefixed_external_groups: set[str] = {
build_ext_group_name_for_onyx(
prefix_group_w_source(
ext_group_name=group_id,
source=source_type,
)

View File

@@ -6,9 +6,8 @@ from sqlalchemy import delete
from sqlalchemy import select
from sqlalchemy.orm import Session
from onyx.access.utils import build_ext_group_name_for_onyx
from onyx.access.utils import prefix_group_w_source
from onyx.configs.constants import DocumentSource
from onyx.db.models import User
from onyx.db.models import User__ExternalUserGroupId
from onyx.db.users import batch_add_ext_perm_user_if_not_exists
from onyx.db.users import get_user_by_email
@@ -62,10 +61,8 @@ def replace_user__ext_group_for_cc_pair(
all_group_member_emails.add(user_email)
# batch add users if they don't exist and get their ids
all_group_members: list[User] = batch_add_ext_perm_user_if_not_exists(
db_session=db_session,
# NOTE: this function handles case sensitivity for emails
emails=list(all_group_member_emails),
all_group_members = batch_add_ext_perm_user_if_not_exists(
db_session=db_session, emails=list(all_group_member_emails)
)
delete_user__ext_group_for_cc_pair__no_commit(
@@ -87,14 +84,12 @@ def replace_user__ext_group_for_cc_pair(
f" with email {user_email} not found"
)
continue
external_group_id = build_ext_group_name_for_onyx(
ext_group_name=external_group.id,
source=source,
)
new_external_permissions.append(
User__ExternalUserGroupId(
user_id=user_id,
external_user_group_id=external_group_id,
external_user_group_id=prefix_group_w_source(
external_group.id, source
),
cc_pair_id=cc_pair_id,
)
)

View File

@@ -2,11 +2,8 @@ from uuid import UUID
from sqlalchemy.orm import Session
from onyx.configs.constants import NotificationType
from onyx.db.models import Persona__User
from onyx.db.models import Persona__UserGroup
from onyx.db.notification import create_notification
from onyx.server.features.persona.models import PersonaSharedNotificationData
def make_persona_private(
@@ -15,9 +12,6 @@ def make_persona_private(
group_ids: list[int] | None,
db_session: Session,
) -> None:
"""NOTE(rkuo): This function batches all updates into a single commit. If we don't
dedupe the inputs, the commit will exception."""
db_session.query(Persona__User).filter(
Persona__User.persona_id == persona_id
).delete(synchronize_session="fetch")
@@ -26,22 +20,11 @@ def make_persona_private(
).delete(synchronize_session="fetch")
if user_ids:
user_ids_set = set(user_ids)
for user_id in user_ids_set:
db_session.add(Persona__User(persona_id=persona_id, user_id=user_id))
create_notification(
user_id=user_id,
notif_type=NotificationType.PERSONA_SHARED,
db_session=db_session,
additional_data=PersonaSharedNotificationData(
persona_id=persona_id,
).model_dump(),
)
for user_uuid in user_ids:
db_session.add(Persona__User(persona_id=persona_id, user_id=user_uuid))
if group_ids:
group_ids_set = set(group_ids)
for group_id in group_ids_set:
for group_id in group_ids:
db_session.add(
Persona__UserGroup(persona_id=persona_id, user_group_id=group_id)
)

View File

@@ -1,138 +1,27 @@
from collections.abc import Sequence
from datetime import datetime
import datetime
from typing import Literal
from sqlalchemy import asc
from sqlalchemy import BinaryExpression
from sqlalchemy import ColumnElement
from sqlalchemy import desc
from sqlalchemy import distinct
from sqlalchemy.orm import contains_eager
from sqlalchemy.orm import joinedload
from sqlalchemy.orm import Session
from sqlalchemy.sql import case
from sqlalchemy.sql import func
from sqlalchemy.sql import select
from sqlalchemy.sql.expression import literal
from sqlalchemy.sql.expression import UnaryExpression
from onyx.configs.constants import QAFeedbackType
from onyx.db.models import ChatMessage
from onyx.db.models import ChatMessageFeedback
from onyx.db.models import ChatSession
def _build_filter_conditions(
start_time: datetime | None,
end_time: datetime | None,
feedback_filter: QAFeedbackType | None,
) -> list[ColumnElement]:
"""
Helper function to build all filter conditions for chat sessions.
Filters by start and end time, feedback type, and any sessions without messages.
start_time: Date from which to filter
end_time: Date to which to filter
feedback_filter: Feedback type to filter by
Returns: List of filter conditions
"""
conditions = []
if start_time is not None:
conditions.append(ChatSession.time_created >= start_time)
if end_time is not None:
conditions.append(ChatSession.time_created <= end_time)
if feedback_filter is not None:
feedback_subq = (
select(ChatMessage.chat_session_id)
.join(ChatMessageFeedback)
.group_by(ChatMessage.chat_session_id)
.having(
case(
(
case(
{literal(feedback_filter == QAFeedbackType.LIKE): True},
else_=False,
),
func.bool_and(ChatMessageFeedback.is_positive),
),
(
case(
{literal(feedback_filter == QAFeedbackType.DISLIKE): True},
else_=False,
),
func.bool_and(func.not_(ChatMessageFeedback.is_positive)),
),
else_=func.bool_or(ChatMessageFeedback.is_positive)
& func.bool_or(func.not_(ChatMessageFeedback.is_positive)),
)
)
)
conditions.append(ChatSession.id.in_(feedback_subq))
return conditions
def get_total_filtered_chat_sessions_count(
db_session: Session,
start_time: datetime | None,
end_time: datetime | None,
feedback_filter: QAFeedbackType | None,
) -> int:
conditions = _build_filter_conditions(start_time, end_time, feedback_filter)
stmt = (
select(func.count(distinct(ChatSession.id)))
.select_from(ChatSession)
.filter(*conditions)
)
return db_session.scalar(stmt) or 0
def get_page_of_chat_sessions(
start_time: datetime | None,
end_time: datetime | None,
db_session: Session,
page_num: int,
page_size: int,
feedback_filter: QAFeedbackType | None = None,
) -> Sequence[ChatSession]:
conditions = _build_filter_conditions(start_time, end_time, feedback_filter)
subquery = (
select(ChatSession.id)
.filter(*conditions)
.order_by(desc(ChatSession.time_created), ChatSession.id)
.limit(page_size)
.offset(page_num * page_size)
.subquery()
)
stmt = (
select(ChatSession)
.join(subquery, ChatSession.id == subquery.c.id)
.outerjoin(ChatMessage, ChatSession.id == ChatMessage.chat_session_id)
.options(
joinedload(ChatSession.user),
joinedload(ChatSession.persona),
contains_eager(ChatSession.messages).joinedload(
ChatMessage.chat_message_feedbacks
),
)
.order_by(
desc(ChatSession.time_created),
ChatSession.id,
asc(ChatMessage.id), # Ensure chronological message order
)
)
return db_session.scalars(stmt).unique().all()
SortByOptions = Literal["time_sent"]
def fetch_chat_sessions_eagerly_by_time(
start: datetime,
end: datetime,
start: datetime.datetime,
end: datetime.datetime,
db_session: Session,
limit: int | None = 500,
initial_time: datetime | None = None,
initial_time: datetime.datetime | None = None,
) -> list[ChatSession]:
time_order: UnaryExpression = desc(ChatSession.time_created)
message_order: UnaryExpression = asc(ChatMessage.id)

View File

@@ -111,10 +111,10 @@ def insert_user_group_token_rate_limit(
return token_limit
def fetch_user_group_token_rate_limits_for_user(
def fetch_user_group_token_rate_limits(
db_session: Session,
group_id: int,
user: User | None,
user: User | None = None,
enabled_only: bool = False,
ordered: bool = True,
get_editable: bool = True,

View File

@@ -218,14 +218,14 @@ def fetch_user_groups_for_user(
return db_session.scalars(stmt).all()
def construct_document_id_select_by_usergroup(
def construct_document_select_by_usergroup(
user_group_id: int,
) -> Select:
"""This returns a statement that should be executed using
.yield_per() to minimize overhead. The primary consumers of this function
are background processing task generators."""
stmt = (
select(Document.id)
select(Document)
.join(
DocumentByConnectorCredentialPair,
Document.id == DocumentByConnectorCredentialPair.id,
@@ -374,9 +374,7 @@ def _add_user_group__cc_pair_relationships__no_commit(
def insert_user_group(db_session: Session, user_group: UserGroupCreate) -> UserGroup:
db_user_group = UserGroup(
name=user_group.name, time_last_modified_by_user=func.now()
)
db_user_group = UserGroup(name=user_group.name)
db_session.add(db_user_group)
db_session.flush() # give the group an ID
@@ -632,10 +630,6 @@ def update_user_group(
select(User).where(User.id.in_(removed_user_ids)) # type: ignore
).unique()
_validate_curator_status__no_commit(db_session, list(removed_users))
# update "time_updated" to now
db_user_group.time_last_modified_by_user = func.now()
db_session.commit()
return db_user_group
@@ -705,10 +699,7 @@ def delete_user_group_cc_pair_relationship__no_commit(
connector_credential_pair_id matches the given cc_pair_id.
Should be used very carefully (only for connectors that are being deleted)."""
cc_pair = get_connector_credential_pair_from_id(
db_session=db_session,
cc_pair_id=cc_pair_id,
)
cc_pair = get_connector_credential_pair_from_id(cc_pair_id, db_session)
if not cc_pair:
raise ValueError(f"Connector Credential Pair '{cc_pair_id}' does not exist")

View File

@@ -13,7 +13,6 @@ from onyx.connectors.confluence.onyx_confluence import OnyxConfluence
from onyx.connectors.confluence.utils import get_user_email_from_username__server
from onyx.connectors.models import SlimDocument
from onyx.db.models import ConnectorCredentialPair
from onyx.indexing.indexing_heartbeat import IndexingHeartbeatInterface
from onyx.utils.logger import setup_logger
logger = setup_logger()
@@ -258,7 +257,6 @@ def _fetch_all_page_restrictions(
slim_docs: list[SlimDocument],
space_permissions_by_space_key: dict[str, ExternalAccess],
is_cloud: bool,
callback: IndexingHeartbeatInterface | None,
) -> list[DocExternalAccess]:
"""
For all pages, if a page has restrictions, then use those restrictions.
@@ -267,12 +265,6 @@ def _fetch_all_page_restrictions(
document_restrictions: list[DocExternalAccess] = []
for slim_doc in slim_docs:
if callback:
if callback.should_stop():
raise RuntimeError("confluence_doc_sync: Stop signal detected")
callback.progress("confluence_doc_sync:fetch_all_page_restrictions", 1)
if slim_doc.perm_sync_data is None:
raise ValueError(
f"No permission sync data found for document {slim_doc.id}"
@@ -342,7 +334,7 @@ def _fetch_all_page_restrictions(
def confluence_doc_sync(
cc_pair: ConnectorCredentialPair, callback: IndexingHeartbeatInterface | None
cc_pair: ConnectorCredentialPair,
) -> list[DocExternalAccess]:
"""
Adds the external permissions to the documents in postgres
@@ -365,16 +357,8 @@ def confluence_doc_sync(
slim_docs = []
logger.debug("Fetching all slim documents from confluence")
for doc_batch in confluence_connector.retrieve_all_slim_documents(
callback=callback
):
for doc_batch in confluence_connector.retrieve_all_slim_documents():
logger.debug(f"Got {len(doc_batch)} slim documents from confluence")
if callback:
if callback.should_stop():
raise RuntimeError("confluence_doc_sync: Stop signal detected")
callback.progress("confluence_doc_sync", 1)
slim_docs.extend(doc_batch)
logger.debug("Fetching all page restrictions for space")
@@ -383,5 +367,4 @@ def confluence_doc_sync(
slim_docs=slim_docs,
space_permissions_by_space_key=space_permissions_by_space_key,
is_cloud=is_cloud,
callback=callback,
)

View File

@@ -1,6 +1,5 @@
from ee.onyx.db.external_perm import ExternalUserGroup
from ee.onyx.external_permissions.confluence.constants import ALL_CONF_EMAILS_GROUP_NAME
from onyx.background.error_logging import emit_background_error
from onyx.connectors.confluence.onyx_confluence import build_confluence_client
from onyx.connectors.confluence.onyx_confluence import OnyxConfluence
from onyx.connectors.confluence.utils import get_user_email_from_username__server
@@ -11,51 +10,33 @@ logger = setup_logger()
def _build_group_member_email_map(
confluence_client: OnyxConfluence, cc_pair_id: int
confluence_client: OnyxConfluence,
) -> dict[str, set[str]]:
group_member_emails: dict[str, set[str]] = {}
for user in confluence_client.paginated_cql_user_retrieval():
logger.debug(f"Processing groups for user: {user}")
email = user.email
for user_result in confluence_client.paginated_cql_user_retrieval():
user = user_result.get("user", {})
if not user:
logger.warning(f"user result missing user field: {user_result}")
continue
email = user.get("email")
if not email:
# This field is only present in Confluence Server
user_name = user.username
user_name = user.get("username")
# If it is present, try to get the email using a Server-specific method
if user_name:
email = get_user_email_from_username__server(
confluence_client=confluence_client,
user_name=user_name,
)
if not email:
# If we still don't have an email, skip this user
msg = f"user result missing email field: {user}"
if user.type == "app":
logger.warning(msg)
else:
emit_background_error(msg, cc_pair_id=cc_pair_id)
logger.error(msg)
logger.warning(f"user result missing email field: {user_result}")
continue
all_users_groups: set[str] = set()
for group in confluence_client.paginated_groups_by_user_retrieval(user.user_id):
for group in confluence_client.paginated_groups_by_user_retrieval(user):
# group name uniqueness is enforced by Confluence, so we can use it as a group ID
group_id = group["name"]
group_member_emails.setdefault(group_id, set()).add(email)
all_users_groups.add(group_id)
if not all_users_groups:
msg = f"No groups found for user with email: {email}"
emit_background_error(msg, cc_pair_id=cc_pair_id)
logger.error(msg)
else:
logger.debug(f"Found groups {all_users_groups} for user with email {email}")
if not group_member_emails:
msg = "No groups found for any users."
emit_background_error(msg, cc_pair_id=cc_pair_id)
logger.error(msg)
return group_member_emails
@@ -71,7 +52,6 @@ def confluence_group_sync(
group_member_email_map = _build_group_member_email_map(
confluence_client=confluence_client,
cc_pair_id=cc_pair.id,
)
onyx_groups: list[ExternalUserGroup] = []
all_found_emails = set()

View File

@@ -6,7 +6,6 @@ from onyx.access.models import ExternalAccess
from onyx.connectors.gmail.connector import GmailConnector
from onyx.connectors.interfaces import GenerateSlimDocumentOutput
from onyx.db.models import ConnectorCredentialPair
from onyx.indexing.indexing_heartbeat import IndexingHeartbeatInterface
from onyx.utils.logger import setup_logger
logger = setup_logger()
@@ -15,7 +14,6 @@ logger = setup_logger()
def _get_slim_doc_generator(
cc_pair: ConnectorCredentialPair,
gmail_connector: GmailConnector,
callback: IndexingHeartbeatInterface | None = None,
) -> GenerateSlimDocumentOutput:
current_time = datetime.now(timezone.utc)
start_time = (
@@ -25,14 +23,12 @@ def _get_slim_doc_generator(
)
return gmail_connector.retrieve_all_slim_documents(
start=start_time,
end=current_time.timestamp(),
callback=callback,
start=start_time, end=current_time.timestamp()
)
def gmail_doc_sync(
cc_pair: ConnectorCredentialPair, callback: IndexingHeartbeatInterface | None
cc_pair: ConnectorCredentialPair,
) -> list[DocExternalAccess]:
"""
Adds the external permissions to the documents in postgres
@@ -43,19 +39,11 @@ def gmail_doc_sync(
gmail_connector = GmailConnector(**cc_pair.connector.connector_specific_config)
gmail_connector.load_credentials(cc_pair.credential.credential_json)
slim_doc_generator = _get_slim_doc_generator(
cc_pair, gmail_connector, callback=callback
)
slim_doc_generator = _get_slim_doc_generator(cc_pair, gmail_connector)
document_external_access: list[DocExternalAccess] = []
for slim_doc_batch in slim_doc_generator:
for slim_doc in slim_doc_batch:
if callback:
if callback.should_stop():
raise RuntimeError("gmail_doc_sync: Stop signal detected")
callback.progress("gmail_doc_sync", 1)
if slim_doc.perm_sync_data is None:
logger.warning(f"No permissions found for document {slim_doc.id}")
continue

View File

@@ -10,7 +10,6 @@ from onyx.connectors.google_utils.resources import get_drive_service
from onyx.connectors.interfaces import GenerateSlimDocumentOutput
from onyx.connectors.models import SlimDocument
from onyx.db.models import ConnectorCredentialPair
from onyx.indexing.indexing_heartbeat import IndexingHeartbeatInterface
from onyx.utils.logger import setup_logger
logger = setup_logger()
@@ -21,7 +20,6 @@ _PERMISSION_ID_PERMISSION_MAP: dict[str, dict[str, Any]] = {}
def _get_slim_doc_generator(
cc_pair: ConnectorCredentialPair,
google_drive_connector: GoogleDriveConnector,
callback: IndexingHeartbeatInterface | None = None,
) -> GenerateSlimDocumentOutput:
current_time = datetime.now(timezone.utc)
start_time = (
@@ -31,9 +29,7 @@ def _get_slim_doc_generator(
)
return google_drive_connector.retrieve_all_slim_documents(
start=start_time,
end=current_time.timestamp(),
callback=callback,
start=start_time, end=current_time.timestamp()
)
@@ -46,33 +42,34 @@ def _fetch_permissions_for_permission_ids(
if not permission_info or not doc_id:
return []
# Check cache first for all permission IDs
permissions = [
_PERMISSION_ID_PERMISSION_MAP[pid]
for pid in permission_ids
if pid in _PERMISSION_ID_PERMISSION_MAP
]
# If we found all permissions in cache, return them
if len(permissions) == len(permission_ids):
return permissions
owner_email = permission_info.get("owner_email")
drive_service = get_drive_service(
creds=google_drive_connector.creds,
user_email=(owner_email or google_drive_connector.primary_admin_email),
)
# We continue on 404 or 403 because the document may not exist or the user may not have access to it
# Otherwise, fetch all permissions and update cache
fetched_permissions = execute_paginated_retrieval(
retrieval_function=drive_service.permissions().list,
list_key="permissions",
fileId=doc_id,
fields="permissions(id, emailAddress, type, domain)",
supportsAllDrives=True,
continue_on_404_or_403=True,
)
permissions_for_doc_id = []
# Update cache and return all permissions
for permission in fetched_permissions:
permissions_for_doc_id.append(permission)
_PERMISSION_ID_PERMISSION_MAP[permission["id"]] = permission
@@ -106,13 +103,7 @@ def _get_permissions_from_slim_doc(
user_emails: set[str] = set()
group_emails: set[str] = set()
public = False
skipped_permissions = 0
for permission in permissions_list:
if not permission:
skipped_permissions += 1
continue
permission_type = permission["type"]
if permission_type == "user":
user_emails.add(permission["emailAddress"])
@@ -129,23 +120,15 @@ def _get_permissions_from_slim_doc(
elif permission_type == "anyone":
public = True
if skipped_permissions > 0:
logger.warning(
f"Skipped {skipped_permissions} permissions of {len(permissions_list)} for document {slim_doc.id}"
)
drive_id = permission_info.get("drive_id")
group_ids = group_emails | ({drive_id} if drive_id is not None else set())
return ExternalAccess(
external_user_emails=user_emails,
external_user_group_ids=group_ids,
external_user_group_ids=group_emails,
is_public=public,
)
def gdrive_doc_sync(
cc_pair: ConnectorCredentialPair, callback: IndexingHeartbeatInterface | None
cc_pair: ConnectorCredentialPair,
) -> list[DocExternalAccess]:
"""
Adds the external permissions to the documents in postgres
@@ -163,12 +146,6 @@ def gdrive_doc_sync(
document_external_accesses = []
for slim_doc_batch in slim_doc_generator:
for slim_doc in slim_doc_batch:
if callback:
if callback.should_stop():
raise RuntimeError("gdrive_doc_sync: Stop signal detected")
callback.progress("gdrive_doc_sync", 1)
ext_access = _get_permissions_from_slim_doc(
google_drive_connector=google_drive_connector,
slim_doc=slim_doc,

View File

@@ -1,127 +1,16 @@
from ee.onyx.db.external_perm import ExternalUserGroup
from onyx.connectors.google_drive.connector import GoogleDriveConnector
from onyx.connectors.google_utils.google_utils import execute_paginated_retrieval
from onyx.connectors.google_utils.resources import AdminService
from onyx.connectors.google_utils.resources import get_admin_service
from onyx.connectors.google_utils.resources import get_drive_service
from onyx.db.models import ConnectorCredentialPair
from onyx.utils.logger import setup_logger
logger = setup_logger()
def _get_drive_members(
google_drive_connector: GoogleDriveConnector,
) -> dict[str, tuple[set[str], set[str]]]:
"""
This builds a map of drive ids to their members (group and user emails).
E.g. {
"drive_id_1": ({"group_email_1"}, {"user_email_1", "user_email_2"}),
"drive_id_2": ({"group_email_3"}, {"user_email_3"}),
}
"""
drive_ids = google_drive_connector.get_all_drive_ids()
drive_id_to_members_map: dict[str, tuple[set[str], set[str]]] = {}
drive_service = get_drive_service(
google_drive_connector.creds,
google_drive_connector.primary_admin_email,
)
for drive_id in drive_ids:
group_emails: set[str] = set()
user_emails: set[str] = set()
for permission in execute_paginated_retrieval(
drive_service.permissions().list,
list_key="permissions",
fileId=drive_id,
fields="permissions(emailAddress, type)",
supportsAllDrives=True,
):
if permission["type"] == "group":
group_emails.add(permission["emailAddress"])
elif permission["type"] == "user":
user_emails.add(permission["emailAddress"])
drive_id_to_members_map[drive_id] = (group_emails, user_emails)
return drive_id_to_members_map
def _get_all_groups(
admin_service: AdminService,
google_domain: str,
) -> set[str]:
"""
This gets all the group emails.
"""
group_emails: set[str] = set()
for group in execute_paginated_retrieval(
admin_service.groups().list,
list_key="groups",
domain=google_domain,
fields="groups(email)",
):
group_emails.add(group["email"])
return group_emails
def _map_group_email_to_member_emails(
admin_service: AdminService,
group_emails: set[str],
) -> dict[str, set[str]]:
"""
This maps group emails to their member emails.
"""
group_to_member_map: dict[str, set[str]] = {}
for group_email in group_emails:
group_member_emails: set[str] = set()
for member in execute_paginated_retrieval(
admin_service.members().list,
list_key="members",
groupKey=group_email,
fields="members(email)",
):
group_member_emails.add(member["email"])
group_to_member_map[group_email] = group_member_emails
return group_to_member_map
def _build_onyx_groups(
drive_id_to_members_map: dict[str, tuple[set[str], set[str]]],
group_email_to_member_emails_map: dict[str, set[str]],
) -> list[ExternalUserGroup]:
onyx_groups: list[ExternalUserGroup] = []
# Convert all drive member definitions to onyx groups
# This is because having drive level access means you have
# irrevocable access to all the files in the drive.
for drive_id, (group_emails, user_emails) in drive_id_to_members_map.items():
all_member_emails: set[str] = user_emails
for group_email in group_emails:
all_member_emails.update(group_email_to_member_emails_map[group_email])
onyx_groups.append(
ExternalUserGroup(
id=drive_id,
user_emails=list(all_member_emails),
)
)
# Convert all group member definitions to onyx groups
for group_email, member_emails in group_email_to_member_emails_map.items():
onyx_groups.append(
ExternalUserGroup(
id=group_email,
user_emails=list(member_emails),
)
)
return onyx_groups
def gdrive_group_sync(
cc_pair: ConnectorCredentialPair,
) -> list[ExternalUserGroup]:
# Initialize connector and build credential/service objects
google_drive_connector = GoogleDriveConnector(
**cc_pair.connector.connector_specific_config
)
@@ -130,23 +19,34 @@ def gdrive_group_sync(
google_drive_connector.creds, google_drive_connector.primary_admin_email
)
# Get all drive members
drive_id_to_members_map = _get_drive_members(google_drive_connector)
onyx_groups: list[ExternalUserGroup] = []
for group in execute_paginated_retrieval(
admin_service.groups().list,
list_key="groups",
domain=google_drive_connector.google_domain,
fields="groups(email)",
):
# The id is the group email
group_email = group["email"]
# Get all group emails
all_group_emails = _get_all_groups(
admin_service, google_drive_connector.google_domain
)
# Gather group member emails
group_member_emails: list[str] = []
for member in execute_paginated_retrieval(
admin_service.members().list,
list_key="members",
groupKey=group_email,
fields="members(email)",
):
group_member_emails.append(member["email"])
# Map group emails to their members
group_email_to_member_emails_map = _map_group_email_to_member_emails(
admin_service, all_group_emails
)
if not group_member_emails:
continue
# Convert the maps to onyx groups
onyx_groups = _build_onyx_groups(
drive_id_to_members_map=drive_id_to_members_map,
group_email_to_member_emails_map=group_email_to_member_emails_map,
)
onyx_groups.append(
ExternalUserGroup(
id=group_email,
user_emails=list(group_member_emails),
)
)
return onyx_groups

View File

@@ -161,10 +161,7 @@ def _get_salesforce_client_for_doc_id(db_session: Session, doc_id: str) -> Sales
cc_pair_id = _DOC_ID_TO_CC_PAIR_ID_MAP[doc_id]
if cc_pair_id not in _CC_PAIR_ID_SALESFORCE_CLIENT_MAP:
cc_pair = get_connector_credential_pair_from_id(
db_session=db_session,
cc_pair_id=cc_pair_id,
)
cc_pair = get_connector_credential_pair_from_id(cc_pair_id, db_session)
if cc_pair is None:
raise ValueError(f"CC pair {cc_pair_id} not found")
credential_json = cc_pair.credential.credential_json

View File

@@ -5,9 +5,8 @@ from onyx.access.models import DocExternalAccess
from onyx.access.models import ExternalAccess
from onyx.connectors.slack.connector import get_channels
from onyx.connectors.slack.connector import make_paginated_slack_api_call_w_retries
from onyx.connectors.slack.connector import SlackConnector
from onyx.connectors.slack.connector import SlackPollConnector
from onyx.db.models import ConnectorCredentialPair
from onyx.indexing.indexing_heartbeat import IndexingHeartbeatInterface
from onyx.utils.logger import setup_logger
@@ -15,12 +14,12 @@ logger = setup_logger()
def _get_slack_document_ids_and_channels(
cc_pair: ConnectorCredentialPair, callback: IndexingHeartbeatInterface | None
cc_pair: ConnectorCredentialPair,
) -> dict[str, list[str]]:
slack_connector = SlackConnector(**cc_pair.connector.connector_specific_config)
slack_connector = SlackPollConnector(**cc_pair.connector.connector_specific_config)
slack_connector.load_credentials(cc_pair.credential.credential_json)
slim_doc_generator = slack_connector.retrieve_all_slim_documents(callback=callback)
slim_doc_generator = slack_connector.retrieve_all_slim_documents()
channel_doc_map: dict[str, list[str]] = {}
for doc_metadata_batch in slim_doc_generator:
@@ -32,14 +31,6 @@ def _get_slack_document_ids_and_channels(
channel_doc_map[channel_id] = []
channel_doc_map[channel_id].append(doc_metadata.id)
if callback:
if callback.should_stop():
raise RuntimeError(
"_get_slack_document_ids_and_channels: Stop signal detected"
)
callback.progress("_get_slack_document_ids_and_channels", 1)
return channel_doc_map
@@ -123,7 +114,7 @@ def _fetch_channel_permissions(
def slack_doc_sync(
cc_pair: ConnectorCredentialPair, callback: IndexingHeartbeatInterface | None
cc_pair: ConnectorCredentialPair,
) -> list[DocExternalAccess]:
"""
Adds the external permissions to the documents in postgres
@@ -136,7 +127,7 @@ def slack_doc_sync(
)
user_id_to_email_map = fetch_user_id_to_email_map(slack_client)
channel_doc_map = _get_slack_document_ids_and_channels(
cc_pair=cc_pair, callback=callback
cc_pair=cc_pair,
)
workspace_permissions = _fetch_workspace_permissions(
user_id_to_email_map=user_id_to_email_map,

View File

@@ -15,13 +15,11 @@ from ee.onyx.external_permissions.slack.doc_sync import slack_doc_sync
from onyx.access.models import DocExternalAccess
from onyx.configs.constants import DocumentSource
from onyx.db.models import ConnectorCredentialPair
from onyx.indexing.indexing_heartbeat import IndexingHeartbeatInterface
# Defining the input/output types for the sync functions
DocSyncFuncType = Callable[
[
ConnectorCredentialPair,
IndexingHeartbeatInterface | None,
],
list[DocExternalAccess],
]

View File

@@ -1,9 +1,7 @@
from fastapi import FastAPI
from httpx_oauth.clients.google import GoogleOAuth2
from httpx_oauth.clients.openid import BASE_SCOPES
from httpx_oauth.clients.openid import OpenID
from ee.onyx.configs.app_configs import OIDC_SCOPE_OVERRIDE
from ee.onyx.configs.app_configs import OPENID_CONFIG_URL
from ee.onyx.server.analytics.api import router as analytics_router
from ee.onyx.server.auth_check import check_ee_router_auth
@@ -90,13 +88,7 @@ def get_application() -> FastAPI:
include_auth_router_with_prefix(
application,
create_onyx_oauth_router(
OpenID(
OAUTH_CLIENT_ID,
OAUTH_CLIENT_SECRET,
OPENID_CONFIG_URL,
# BASE_SCOPES is the same as not setting this
base_scopes=OIDC_SCOPE_OVERRIDE or BASE_SCOPES,
),
OpenID(OAUTH_CLIENT_ID, OAUTH_CLIENT_SECRET, OPENID_CONFIG_URL),
auth_backend,
USER_AUTH_SECRET,
associate_by_email=True,

View File

@@ -80,7 +80,7 @@ def oneoff_standard_answers(
def _handle_standard_answers(
message_info: SlackMessageInfo,
receiver_ids: list[str] | None,
slack_channel_config: SlackChannelConfig,
slack_channel_config: SlackChannelConfig | None,
prompt: Prompt | None,
logger: OnyxLoggingAdapter,
client: WebClient,
@@ -94,10 +94,13 @@ def _handle_standard_answers(
Returns True if standard answers are found to match the user's message and therefore,
we still need to respond to the users.
"""
# if no channel config, then no standard answers are configured
if not slack_channel_config:
return False
slack_thread_id = message_info.thread_to_respond
configured_standard_answer_categories = (
slack_channel_config.standard_answer_categories
slack_channel_config.standard_answer_categories if slack_channel_config else []
)
configured_standard_answers = set(
[
@@ -147,9 +150,9 @@ def _handle_standard_answers(
db_session=db_session,
description="",
user_id=None,
persona_id=(
slack_channel_config.persona.id if slack_channel_config.persona else 0
),
persona_id=slack_channel_config.persona.id
if slack_channel_config.persona
else 0,
onyxbot_flow=True,
slack_thread_id=slack_thread_id,
)
@@ -179,7 +182,7 @@ def _handle_standard_answers(
formatted_answers.append(formatted_answer)
answer_message = "\n\n".join(formatted_answers)
chat_message = create_new_chat_message(
_ = create_new_chat_message(
chat_session_id=chat_session.id,
parent_message=new_user_message,
prompt_id=prompt.id if prompt else None,
@@ -188,13 +191,8 @@ def _handle_standard_answers(
message_type=MessageType.ASSISTANT,
error=None,
db_session=db_session,
commit=False,
commit=True,
)
# attach the standard answers to the chat message
chat_message.standard_answers = [
standard_answer for standard_answer, _ in matching_standard_answers
]
db_session.commit()
update_emote_react(
emoji=DANSWER_REACT_EMOJI,

View File

@@ -228,6 +228,8 @@ def get_assistant_stats(
datetime.datetime.utcnow() - datetime.timedelta(days=_DEFAULT_LOOKBACK_DAYS)
)
end = end or datetime.datetime.utcnow()
print("current user")
print(user)
if not user_can_view_assistant_stats(db_session, user, assistant_id):
raise HTTPException(

View File

@@ -10,7 +10,6 @@ from fastapi import Response
from ee.onyx.auth.users import decode_anonymous_user_jwt_token
from ee.onyx.configs.app_configs import ANONYMOUS_USER_COOKIE_NAME
from onyx.auth.api_key import extract_tenant_from_api_key_header
from onyx.configs.constants import TENANT_ID_COOKIE_NAME
from onyx.db.engine import is_valid_schema_name
from onyx.redis.redis_pool import retrieve_auth_token_data_from_redis
from shared_configs.configs import MULTI_TENANT
@@ -33,7 +32,7 @@ def add_tenant_id_middleware(app: FastAPI, logger: logging.LoggerAdapter) -> Non
return await call_next(request)
except Exception as e:
logger.exception(f"Error in tenant ID middleware: {str(e)}")
logger.error(f"Error in tenant ID middleware: {str(e)}")
raise
@@ -44,12 +43,11 @@ async def _get_tenant_id_from_request(
Attempt to extract tenant_id from:
1) The API key header
2) The Redis-based token (stored in Cookie: fastapiusersauth)
3) Reset token cookie
Fallback: POSTGRES_DEFAULT_SCHEMA
"""
# Check for API key
tenant_id = extract_tenant_from_api_key_header(request)
if tenant_id is not None:
if tenant_id:
return tenant_id
# Check for anonymous user cookie
@@ -64,7 +62,6 @@ async def _get_tenant_id_from_request(
try:
# Look up token data in Redis
token_data = await retrieve_auth_token_data_from_redis(request)
if not token_data:
@@ -88,18 +85,8 @@ async def _get_tenant_id_from_request(
if not is_valid_schema_name(tenant_id):
raise HTTPException(status_code=400, detail="Invalid tenant ID format")
return tenant_id
except Exception as e:
logger.error(f"Unexpected error in _get_tenant_id_from_request: {str(e)}")
raise HTTPException(status_code=500, detail="Internal server error")
finally:
if tenant_id:
return tenant_id
# As a final step, check for explicit tenant_id cookie
tenant_id_cookie = request.cookies.get(TENANT_ID_COOKIE_NAME)
if tenant_id_cookie and is_valid_schema_name(tenant_id_cookie):
return tenant_id_cookie
# If we've reached this point, return the default schema
return POSTGRES_DEFAULT_SCHEMA

View File

@@ -36,12 +36,12 @@ from onyx.connectors.google_utils.shared_constants import (
GoogleOAuthAuthenticationMethod,
)
from onyx.db.credentials import create_credential
from onyx.db.engine import get_current_tenant_id
from onyx.db.engine import get_session
from onyx.db.models import User
from onyx.redis.redis_pool import get_redis_client
from onyx.server.documents.models import CredentialBase
from onyx.utils.logger import setup_logger
from shared_configs.contextvars import get_current_tenant_id
logger = setup_logger()
@@ -271,12 +271,12 @@ def prepare_authorization_request(
connector: DocumentSource,
redirect_on_success: str | None,
user: User = Depends(current_user),
tenant_id: str | None = Depends(get_current_tenant_id),
) -> JSONResponse:
"""Used by the frontend to generate the url for the user's browser during auth request.
Example: https://www.oauth.com/oauth2-servers/authorization/the-authorization-request/
"""
tenant_id = get_current_tenant_id()
# create random oauth state param for security and to retrieve user data later
oauth_uuid = uuid.uuid4()
@@ -286,7 +286,6 @@ def prepare_authorization_request(
oauth_state = (
base64.urlsafe_b64encode(oauth_uuid.bytes).rstrip(b"=").decode("utf-8")
)
session: str
if connector == DocumentSource.SLACK:
oauth_url = SlackOAuth.generate_oauth_url(oauth_state)
@@ -329,6 +328,7 @@ def handle_slack_oauth_callback(
state: str,
user: User = Depends(current_user),
db_session: Session = Depends(get_session),
tenant_id: str | None = Depends(get_current_tenant_id),
) -> JSONResponse:
if not SlackOAuth.CLIENT_ID or not SlackOAuth.CLIENT_SECRET:
raise HTTPException(
@@ -336,7 +336,7 @@ def handle_slack_oauth_callback(
detail="Slack client ID or client secret is not configured.",
)
r = get_redis_client()
r = get_redis_client(tenant_id=tenant_id)
# recover the state
padded_state = state + "=" * (
@@ -522,6 +522,7 @@ def handle_google_drive_oauth_callback(
state: str,
user: User = Depends(current_user),
db_session: Session = Depends(get_session),
tenant_id: str | None = Depends(get_current_tenant_id),
) -> JSONResponse:
if not GoogleDriveOAuth.CLIENT_ID or not GoogleDriveOAuth.CLIENT_SECRET:
raise HTTPException(
@@ -529,7 +530,7 @@ def handle_google_drive_oauth_callback(
detail="Google Drive client ID or client secret is not configured.",
)
r = get_redis_client()
r = get_redis_client(tenant_id=tenant_id)
# recover the state
padded_state = state + "=" * (
@@ -553,7 +554,6 @@ def handle_google_drive_oauth_callback(
)
session_json = session_json_bytes.decode("utf-8")
session: GoogleDriveOAuth.OAuthSession
try:
session = GoogleDriveOAuth.parse_session(session_json)

View File

@@ -125,10 +125,10 @@ class OneShotQARequest(ChunkContext):
# will also disable Thread-based Rewording if specified
query_override: str | None = None
# If True, skips generating an AI response to the search query
# If True, skips generative an AI response to the search query
skip_gen_ai_answer_generation: bool = False
# If True, uses agentic search instead of basic search
# If True, uses pro search instead of basic search
use_agentic_search: bool = False
@model_validator(mode="after")

View File

@@ -83,7 +83,6 @@ def handle_search_request(
user=user,
llm=llm,
fast_llm=fast_llm,
skip_query_analysis=False,
db_session=db_session,
bypass_acl=False,
)
@@ -198,7 +197,6 @@ def get_answer_stream(
rerank_settings=query_request.rerank_settings,
db_session=db_session,
use_agentic_search=query_request.use_agentic_search,
skip_gen_ai_answer_generation=query_request.skip_gen_ai_answer_generation,
)
packets = stream_chat_message_objects(

View File

@@ -13,7 +13,7 @@ from sqlalchemy import select
from sqlalchemy.orm import Session
from onyx.db.api_key import is_api_key_email_address
from onyx.db.engine import get_session_with_current_tenant
from onyx.db.engine import get_session_with_tenant
from onyx.db.models import ChatMessage
from onyx.db.models import ChatSession
from onyx.db.models import TokenRateLimit
@@ -28,21 +28,21 @@ from onyx.server.query_and_chat.token_limit import _user_is_rate_limited_by_glob
from onyx.utils.threadpool_concurrency import run_functions_tuples_in_parallel
def _check_token_rate_limits(user: User | None) -> None:
def _check_token_rate_limits(user: User | None, tenant_id: str | None) -> None:
if user is None:
# Unauthenticated users are only rate limited by global settings
_user_is_rate_limited_by_global()
_user_is_rate_limited_by_global(tenant_id)
elif is_api_key_email_address(user.email):
# API keys are only rate limited by global settings
_user_is_rate_limited_by_global()
_user_is_rate_limited_by_global(tenant_id)
else:
run_functions_tuples_in_parallel(
[
(_user_is_rate_limited, (user.id,)),
(_user_is_rate_limited_by_group, (user.id,)),
(_user_is_rate_limited_by_global, ()),
(_user_is_rate_limited, (user.id, tenant_id)),
(_user_is_rate_limited_by_group, (user.id, tenant_id)),
(_user_is_rate_limited_by_global, (tenant_id,)),
]
)
@@ -52,8 +52,8 @@ User rate limits
"""
def _user_is_rate_limited(user_id: UUID) -> None:
with get_session_with_current_tenant() as db_session:
def _user_is_rate_limited(user_id: UUID, tenant_id: str | None) -> None:
with get_session_with_tenant(tenant_id) as db_session:
user_rate_limits = fetch_all_user_token_rate_limits(
db_session=db_session, enabled_only=True, ordered=False
)
@@ -93,8 +93,8 @@ User Group rate limits
"""
def _user_is_rate_limited_by_group(user_id: UUID) -> None:
with get_session_with_current_tenant() as db_session:
def _user_is_rate_limited_by_group(user_id: UUID, tenant_id: str | None) -> None:
with get_session_with_tenant(tenant_id) as db_session:
group_rate_limits = _fetch_all_user_group_rate_limits(user_id, db_session)
if group_rate_limits:

View File

@@ -1,44 +1,277 @@
import csv
import io
from datetime import datetime
from datetime import timedelta
from datetime import timezone
from http import HTTPStatus
from typing import Literal
from uuid import UUID
from fastapi import APIRouter
from fastapi import Depends
from fastapi import HTTPException
from fastapi import Query
from fastapi.responses import StreamingResponse
from pydantic import BaseModel
from sqlalchemy.orm import Session
from ee.onyx.db.query_history import fetch_chat_sessions_eagerly_by_time
from ee.onyx.db.query_history import get_page_of_chat_sessions
from ee.onyx.db.query_history import get_total_filtered_chat_sessions_count
from ee.onyx.server.query_history.models import ChatSessionMinimal
from ee.onyx.server.query_history.models import ChatSessionSnapshot
from ee.onyx.server.query_history.models import MessageSnapshot
from ee.onyx.server.query_history.models import QuestionAnswerPairSnapshot
from onyx.auth.users import current_admin_user
from onyx.auth.users import get_display_email
from onyx.chat.chat_utils import create_chat_chain
from onyx.configs.app_configs import ONYX_QUERY_HISTORY_TYPE
from onyx.configs.constants import MessageType
from onyx.configs.constants import QAFeedbackType
from onyx.configs.constants import QueryHistoryType
from onyx.configs.constants import SessionType
from onyx.db.chat import get_chat_session_by_id
from onyx.db.chat import get_chat_sessions_by_user
from onyx.db.engine import get_session
from onyx.db.models import ChatMessage
from onyx.db.models import ChatSession
from onyx.db.models import User
from onyx.server.documents.models import PaginatedReturn
from onyx.server.query_and_chat.models import ChatSessionDetails
from onyx.server.query_and_chat.models import ChatSessionsResponse
router = APIRouter()
ONYX_ANONYMIZED_EMAIL = "anonymous@anonymous.invalid"
class AbridgedSearchDoc(BaseModel):
"""A subset of the info present in `SearchDoc`"""
document_id: str
semantic_identifier: str
link: str | None
class MessageSnapshot(BaseModel):
message: str
message_type: MessageType
documents: list[AbridgedSearchDoc]
feedback_type: QAFeedbackType | None
feedback_text: str | None
time_created: datetime
@classmethod
def build(cls, message: ChatMessage) -> "MessageSnapshot":
latest_messages_feedback_obj = (
message.chat_message_feedbacks[-1]
if len(message.chat_message_feedbacks) > 0
else None
)
feedback_type = (
(
QAFeedbackType.LIKE
if latest_messages_feedback_obj.is_positive
else QAFeedbackType.DISLIKE
)
if latest_messages_feedback_obj
else None
)
feedback_text = (
latest_messages_feedback_obj.feedback_text
if latest_messages_feedback_obj
else None
)
return cls(
message=message.message,
message_type=message.message_type,
documents=[
AbridgedSearchDoc(
document_id=document.document_id,
semantic_identifier=document.semantic_id,
link=document.link,
)
for document in message.search_docs
],
feedback_type=feedback_type,
feedback_text=feedback_text,
time_created=message.time_sent,
)
class ChatSessionMinimal(BaseModel):
id: UUID
user_email: str
name: str | None
first_user_message: str
first_ai_message: str
assistant_id: int | None
assistant_name: str | None
time_created: datetime
feedback_type: QAFeedbackType | Literal["mixed"] | None
flow_type: SessionType
conversation_length: int
class ChatSessionSnapshot(BaseModel):
id: UUID
user_email: str
name: str | None
messages: list[MessageSnapshot]
assistant_id: int | None
assistant_name: str | None
time_created: datetime
flow_type: SessionType
class QuestionAnswerPairSnapshot(BaseModel):
chat_session_id: UUID
# 1-indexed message number in the chat_session
# e.g. the first message pair in the chat_session is 1, the second is 2, etc.
message_pair_num: int
user_message: str
ai_response: str
retrieved_documents: list[AbridgedSearchDoc]
feedback_type: QAFeedbackType | None
feedback_text: str | None
persona_name: str | None
user_email: str
time_created: datetime
flow_type: SessionType
@classmethod
def from_chat_session_snapshot(
cls,
chat_session_snapshot: ChatSessionSnapshot,
) -> list["QuestionAnswerPairSnapshot"]:
message_pairs: list[tuple[MessageSnapshot, MessageSnapshot]] = []
for ind in range(1, len(chat_session_snapshot.messages), 2):
message_pairs.append(
(
chat_session_snapshot.messages[ind - 1],
chat_session_snapshot.messages[ind],
)
)
return [
cls(
chat_session_id=chat_session_snapshot.id,
message_pair_num=ind + 1,
user_message=user_message.message,
ai_response=ai_message.message,
retrieved_documents=ai_message.documents,
feedback_type=ai_message.feedback_type,
feedback_text=ai_message.feedback_text,
persona_name=chat_session_snapshot.assistant_name,
user_email=get_display_email(chat_session_snapshot.user_email),
time_created=user_message.time_created,
flow_type=chat_session_snapshot.flow_type,
)
for ind, (user_message, ai_message) in enumerate(message_pairs)
]
def to_json(self) -> dict[str, str | None]:
return {
"chat_session_id": str(self.chat_session_id),
"message_pair_num": str(self.message_pair_num),
"user_message": self.user_message,
"ai_response": self.ai_response,
"retrieved_documents": "|".join(
[
doc.link or doc.semantic_identifier
for doc in self.retrieved_documents
]
),
"feedback_type": self.feedback_type.value if self.feedback_type else "",
"feedback_text": self.feedback_text or "",
"persona_name": self.persona_name,
"user_email": self.user_email,
"time_created": str(self.time_created),
"flow_type": self.flow_type,
}
def determine_flow_type(chat_session: ChatSession) -> SessionType:
return SessionType.SLACK if chat_session.onyxbot_flow else SessionType.CHAT
def fetch_and_process_chat_session_history_minimal(
db_session: Session,
start: datetime,
end: datetime,
feedback_filter: QAFeedbackType | None = None,
limit: int | None = 500,
) -> list[ChatSessionMinimal]:
chat_sessions = fetch_chat_sessions_eagerly_by_time(
start=start, end=end, db_session=db_session, limit=limit
)
minimal_sessions = []
for chat_session in chat_sessions:
if not chat_session.messages:
continue
first_user_message = next(
(
message.message
for message in chat_session.messages
if message.message_type == MessageType.USER
),
"",
)
first_ai_message = next(
(
message.message
for message in chat_session.messages
if message.message_type == MessageType.ASSISTANT
),
"",
)
has_positive_feedback = any(
feedback.is_positive
for message in chat_session.messages
for feedback in message.chat_message_feedbacks
)
has_negative_feedback = any(
not feedback.is_positive
for message in chat_session.messages
for feedback in message.chat_message_feedbacks
)
feedback_type: QAFeedbackType | Literal["mixed"] | None = (
"mixed"
if has_positive_feedback and has_negative_feedback
else QAFeedbackType.LIKE
if has_positive_feedback
else QAFeedbackType.DISLIKE
if has_negative_feedback
else None
)
if feedback_filter:
if feedback_filter == QAFeedbackType.LIKE and not has_positive_feedback:
continue
if feedback_filter == QAFeedbackType.DISLIKE and not has_negative_feedback:
continue
flow_type = determine_flow_type(chat_session)
minimal_sessions.append(
ChatSessionMinimal(
id=chat_session.id,
user_email=get_display_email(
chat_session.user.email if chat_session.user else None
),
name=chat_session.description,
first_user_message=first_user_message,
first_ai_message=first_ai_message,
assistant_id=chat_session.persona_id,
assistant_name=(
chat_session.persona.name if chat_session.persona else None
),
time_created=chat_session.time_created,
feedback_type=feedback_type,
flow_type=flow_type,
conversation_length=len(
[
m
for m in chat_session.messages
if m.message_type != MessageType.SYSTEM
]
),
)
)
return minimal_sessions
def fetch_and_process_chat_session_history(
@@ -86,7 +319,7 @@ def snapshot_from_chat_session(
except RuntimeError:
return None
flow_type = SessionType.SLACK if chat_session.onyxbot_flow else SessionType.CHAT
flow_type = determine_flow_type(chat_session)
return ChatSessionSnapshot(
id=chat_session.id,
@@ -112,17 +345,6 @@ def get_user_chat_sessions(
_: User | None = Depends(current_admin_user),
db_session: Session = Depends(get_session),
) -> ChatSessionsResponse:
# we specifically don't allow this endpoint if "anonymized" since
# this is a direct query on the user id
if ONYX_QUERY_HISTORY_TYPE in [
QueryHistoryType.DISABLED,
QueryHistoryType.ANONYMIZED,
]:
raise HTTPException(
status_code=HTTPStatus.FORBIDDEN,
detail="Per user query history has been disabled by the administrator.",
)
try:
chat_sessions = get_chat_sessions_by_user(
user_id=user_id, deleted=False, db_session=db_session, limit=0
@@ -138,7 +360,6 @@ def get_user_chat_sessions(
name=chat.description,
persona_id=chat.persona_id,
time_created=chat.time_created.isoformat(),
time_updated=chat.time_updated.isoformat(),
shared_status=chat.shared_status,
folder_id=chat.folder_id,
current_alternate_model=chat.current_alternate_model,
@@ -150,49 +371,22 @@ def get_user_chat_sessions(
@router.get("/admin/chat-session-history")
def get_chat_session_history(
page_num: int = Query(0, ge=0),
page_size: int = Query(10, ge=1),
feedback_type: QAFeedbackType | None = None,
start_time: datetime | None = None,
end_time: datetime | None = None,
start: datetime | None = None,
end: datetime | None = None,
_: User | None = Depends(current_admin_user),
db_session: Session = Depends(get_session),
) -> PaginatedReturn[ChatSessionMinimal]:
if ONYX_QUERY_HISTORY_TYPE == QueryHistoryType.DISABLED:
raise HTTPException(
status_code=HTTPStatus.FORBIDDEN,
detail="Query history has been disabled by the administrator.",
)
page_of_chat_sessions = get_page_of_chat_sessions(
page_num=page_num,
page_size=page_size,
) -> list[ChatSessionMinimal]:
return fetch_and_process_chat_session_history_minimal(
db_session=db_session,
start_time=start_time,
end_time=end_time,
start=start
or (
datetime.now(tz=timezone.utc) - timedelta(days=30)
), # default is 30d lookback
end=end or datetime.now(tz=timezone.utc),
feedback_filter=feedback_type,
)
total_filtered_chat_sessions_count = get_total_filtered_chat_sessions_count(
db_session=db_session,
start_time=start_time,
end_time=end_time,
feedback_filter=feedback_type,
)
minimal_chat_sessions: list[ChatSessionMinimal] = []
for chat_session in page_of_chat_sessions:
minimal_chat_session = ChatSessionMinimal.from_chat_session(chat_session)
if ONYX_QUERY_HISTORY_TYPE == QueryHistoryType.ANONYMIZED:
minimal_chat_session.user_email = ONYX_ANONYMIZED_EMAIL
minimal_chat_sessions.append(minimal_chat_session)
return PaginatedReturn(
items=minimal_chat_sessions,
total_items=total_filtered_chat_sessions_count,
)
@router.get("/admin/chat-session-history/{chat_session_id}")
def get_chat_session_admin(
@@ -200,12 +394,6 @@ def get_chat_session_admin(
_: User | None = Depends(current_admin_user),
db_session: Session = Depends(get_session),
) -> ChatSessionSnapshot:
if ONYX_QUERY_HISTORY_TYPE == QueryHistoryType.DISABLED:
raise HTTPException(
status_code=HTTPStatus.FORBIDDEN,
detail="Query history has been disabled by the administrator.",
)
try:
chat_session = get_chat_session_by_id(
chat_session_id=chat_session_id,
@@ -227,9 +415,6 @@ def get_chat_session_admin(
f"Could not create snapshot for chat session with id '{chat_session_id}'",
)
if ONYX_QUERY_HISTORY_TYPE == QueryHistoryType.ANONYMIZED:
snapshot.user_email = ONYX_ANONYMIZED_EMAIL
return snapshot
@@ -240,12 +425,6 @@ def get_query_history_as_csv(
end: datetime | None = None,
db_session: Session = Depends(get_session),
) -> StreamingResponse:
if ONYX_QUERY_HISTORY_TYPE == QueryHistoryType.DISABLED:
raise HTTPException(
status_code=HTTPStatus.FORBIDDEN,
detail="Query history has been disabled by the administrator.",
)
complete_chat_session_history = fetch_and_process_chat_session_history(
db_session=db_session,
start=start or datetime.fromtimestamp(0, tz=timezone.utc),
@@ -256,9 +435,6 @@ def get_query_history_as_csv(
question_answer_pairs: list[QuestionAnswerPairSnapshot] = []
for chat_session_snapshot in complete_chat_session_history:
if ONYX_QUERY_HISTORY_TYPE == QueryHistoryType.ANONYMIZED:
chat_session_snapshot.user_email = ONYX_ANONYMIZED_EMAIL
question_answer_pairs.extend(
QuestionAnswerPairSnapshot.from_chat_session_snapshot(chat_session_snapshot)
)

View File

@@ -1,218 +0,0 @@
from datetime import datetime
from uuid import UUID
from pydantic import BaseModel
from onyx.auth.users import get_display_email
from onyx.configs.constants import MessageType
from onyx.configs.constants import QAFeedbackType
from onyx.configs.constants import SessionType
from onyx.db.models import ChatMessage
from onyx.db.models import ChatSession
class AbridgedSearchDoc(BaseModel):
"""A subset of the info present in `SearchDoc`"""
document_id: str
semantic_identifier: str
link: str | None
class MessageSnapshot(BaseModel):
id: int
message: str
message_type: MessageType
documents: list[AbridgedSearchDoc]
feedback_type: QAFeedbackType | None
feedback_text: str | None
time_created: datetime
@classmethod
def build(cls, message: ChatMessage) -> "MessageSnapshot":
latest_messages_feedback_obj = (
message.chat_message_feedbacks[-1]
if len(message.chat_message_feedbacks) > 0
else None
)
feedback_type = (
(
QAFeedbackType.LIKE
if latest_messages_feedback_obj.is_positive
else QAFeedbackType.DISLIKE
)
if latest_messages_feedback_obj
else None
)
feedback_text = (
latest_messages_feedback_obj.feedback_text
if latest_messages_feedback_obj
else None
)
return cls(
id=message.id,
message=message.message,
message_type=message.message_type,
documents=[
AbridgedSearchDoc(
document_id=document.document_id,
semantic_identifier=document.semantic_id,
link=document.link,
)
for document in message.search_docs
],
feedback_type=feedback_type,
feedback_text=feedback_text,
time_created=message.time_sent,
)
class ChatSessionMinimal(BaseModel):
id: UUID
user_email: str
name: str | None
first_user_message: str
first_ai_message: str
assistant_id: int | None
assistant_name: str | None
time_created: datetime
feedback_type: QAFeedbackType | None
flow_type: SessionType
conversation_length: int
@classmethod
def from_chat_session(cls, chat_session: ChatSession) -> "ChatSessionMinimal":
first_user_message = next(
(
message.message
for message in chat_session.messages
if message.message_type == MessageType.USER
),
"",
)
first_ai_message = next(
(
message.message
for message in chat_session.messages
if message.message_type == MessageType.ASSISTANT
),
"",
)
list_of_message_feedbacks = [
feedback.is_positive
for message in chat_session.messages
for feedback in message.chat_message_feedbacks
]
session_feedback_type = None
if list_of_message_feedbacks:
if all(list_of_message_feedbacks):
session_feedback_type = QAFeedbackType.LIKE
elif not any(list_of_message_feedbacks):
session_feedback_type = QAFeedbackType.DISLIKE
else:
session_feedback_type = QAFeedbackType.MIXED
return cls(
id=chat_session.id,
user_email=get_display_email(
chat_session.user.email if chat_session.user else None
),
name=chat_session.description,
first_user_message=first_user_message,
first_ai_message=first_ai_message,
assistant_id=chat_session.persona_id,
assistant_name=(
chat_session.persona.name if chat_session.persona else None
),
time_created=chat_session.time_created,
feedback_type=session_feedback_type,
flow_type=SessionType.SLACK
if chat_session.onyxbot_flow
else SessionType.CHAT,
conversation_length=len(
[
message
for message in chat_session.messages
if message.message_type != MessageType.SYSTEM
]
),
)
class ChatSessionSnapshot(BaseModel):
id: UUID
user_email: str
name: str | None
messages: list[MessageSnapshot]
assistant_id: int | None
assistant_name: str | None
time_created: datetime
flow_type: SessionType
class QuestionAnswerPairSnapshot(BaseModel):
chat_session_id: UUID
# 1-indexed message number in the chat_session
# e.g. the first message pair in the chat_session is 1, the second is 2, etc.
message_pair_num: int
user_message: str
ai_response: str
retrieved_documents: list[AbridgedSearchDoc]
feedback_type: QAFeedbackType | None
feedback_text: str | None
persona_name: str | None
user_email: str
time_created: datetime
flow_type: SessionType
@classmethod
def from_chat_session_snapshot(
cls,
chat_session_snapshot: ChatSessionSnapshot,
) -> list["QuestionAnswerPairSnapshot"]:
message_pairs: list[tuple[MessageSnapshot, MessageSnapshot]] = []
for ind in range(1, len(chat_session_snapshot.messages), 2):
message_pairs.append(
(
chat_session_snapshot.messages[ind - 1],
chat_session_snapshot.messages[ind],
)
)
return [
cls(
chat_session_id=chat_session_snapshot.id,
message_pair_num=ind + 1,
user_message=user_message.message,
ai_response=ai_message.message,
retrieved_documents=ai_message.documents,
feedback_type=ai_message.feedback_type,
feedback_text=ai_message.feedback_text,
persona_name=chat_session_snapshot.assistant_name,
user_email=get_display_email(chat_session_snapshot.user_email),
time_created=user_message.time_created,
flow_type=chat_session_snapshot.flow_type,
)
for ind, (user_message, ai_message) in enumerate(message_pairs)
]
def to_json(self) -> dict[str, str | None]:
return {
"chat_session_id": str(self.chat_session_id),
"message_pair_num": str(self.message_pair_num),
"user_message": self.user_message,
"ai_response": self.ai_response,
"retrieved_documents": "|".join(
[
doc.link or doc.semantic_identifier
for doc in self.retrieved_documents
]
),
"feedback_type": self.feedback_type.value if self.feedback_type else "",
"feedback_text": self.feedback_text or "",
"persona_name": self.persona_name,
"user_email": self.user_email,
"time_created": str(self.time_created),
"flow_type": self.flow_type,
}

View File

@@ -24,7 +24,7 @@ from onyx.db.llm import update_default_provider
from onyx.db.llm import upsert_llm_provider
from onyx.db.models import Tool
from onyx.db.persona import upsert_persona
from onyx.server.features.persona.models import PersonaUpsertRequest
from onyx.server.features.persona.models import CreatePersonaRequest
from onyx.server.manage.llm.models import LLMProviderUpsertRequest
from onyx.server.settings.models import Settings
from onyx.server.settings.store import store_settings as store_base_settings
@@ -57,7 +57,7 @@ class SeedConfiguration(BaseModel):
llms: list[LLMProviderUpsertRequest] | None = None
admin_user_emails: list[str] | None = None
seeded_logo_path: str | None = None
personas: list[PersonaUpsertRequest] | None = None
personas: list[CreatePersonaRequest] | None = None
settings: Settings | None = None
enterprise_settings: EnterpriseSettings | None = None
@@ -128,7 +128,7 @@ def _seed_llms(
)
def _seed_personas(db_session: Session, personas: list[PersonaUpsertRequest]) -> None:
def _seed_personas(db_session: Session, personas: list[CreatePersonaRequest]) -> None:
if personas:
logger.notice("Seeding Personas")
for persona in personas:

View File

@@ -18,16 +18,11 @@ from ee.onyx.server.tenants.anonymous_user_path import (
from ee.onyx.server.tenants.anonymous_user_path import modify_anonymous_user_path
from ee.onyx.server.tenants.anonymous_user_path import validate_anonymous_user_path
from ee.onyx.server.tenants.billing import fetch_billing_information
from ee.onyx.server.tenants.billing import fetch_stripe_checkout_session
from ee.onyx.server.tenants.billing import fetch_tenant_stripe_information
from ee.onyx.server.tenants.models import AnonymousUserPath
from ee.onyx.server.tenants.models import BillingInformation
from ee.onyx.server.tenants.models import ImpersonateRequest
from ee.onyx.server.tenants.models import ProductGatingRequest
from ee.onyx.server.tenants.models import ProductGatingResponse
from ee.onyx.server.tenants.models import SubscriptionSessionResponse
from ee.onyx.server.tenants.models import SubscriptionStatusResponse
from ee.onyx.server.tenants.product_gating import store_product_gating
from ee.onyx.server.tenants.provisioning import delete_user_from_control_plane
from ee.onyx.server.tenants.user_mapping import get_tenant_id_for_email
from ee.onyx.server.tenants.user_mapping import remove_all_users_from_tenant
@@ -39,17 +34,18 @@ from onyx.auth.users import get_redis_strategy
from onyx.auth.users import optional_user
from onyx.auth.users import User
from onyx.configs.app_configs import WEB_DOMAIN
from onyx.configs.constants import FASTAPI_USERS_AUTH_COOKIE_NAME
from onyx.db.auth import get_user_count
from onyx.db.engine import get_current_tenant_id
from onyx.db.engine import get_session
from onyx.db.engine import get_session_with_shared_schema
from onyx.db.engine import get_session_with_tenant
from onyx.db.notification import create_notification
from onyx.db.users import delete_user_from_db
from onyx.db.users import get_user_by_email
from onyx.server.manage.models import UserByEmail
from onyx.server.settings.store import load_settings
from onyx.server.settings.store import store_settings
from onyx.utils.logger import setup_logger
from shared_configs.contextvars import CURRENT_TENANT_ID_CONTEXTVAR
from shared_configs.contextvars import get_current_tenant_id
stripe.api_key = STRIPE_SECRET_KEY
logger = setup_logger()
@@ -58,14 +54,13 @@ router = APIRouter(prefix="/tenants")
@router.get("/anonymous-user-path")
async def get_anonymous_user_path_api(
tenant_id: str | None = Depends(get_current_tenant_id),
_: User | None = Depends(current_admin_user),
) -> AnonymousUserPath:
tenant_id = get_current_tenant_id()
if tenant_id is None:
raise HTTPException(status_code=404, detail="Tenant not found")
with get_session_with_shared_schema() as db_session:
with get_session_with_tenant(tenant_id=None) as db_session:
current_path = get_anonymous_user_path(tenant_id, db_session)
return AnonymousUserPath(anonymous_user_path=current_path)
@@ -74,15 +69,15 @@ async def get_anonymous_user_path_api(
@router.post("/anonymous-user-path")
async def set_anonymous_user_path_api(
anonymous_user_path: str,
tenant_id: str = Depends(get_current_tenant_id),
_: User | None = Depends(current_admin_user),
) -> None:
tenant_id = get_current_tenant_id()
try:
validate_anonymous_user_path(anonymous_user_path)
except ValueError as e:
raise HTTPException(status_code=400, detail=str(e))
with get_session_with_shared_schema() as db_session:
with get_session_with_tenant(tenant_id=None) as db_session:
try:
modify_anonymous_user_path(tenant_id, anonymous_user_path, db_session)
except IntegrityError:
@@ -103,7 +98,7 @@ async def login_as_anonymous_user(
anonymous_user_path: str,
_: User | None = Depends(optional_user),
) -> Response:
with get_session_with_shared_schema() as db_session:
with get_session_with_tenant(tenant_id=None) as db_session:
tenant_id = get_tenant_id_for_anonymous_user_path(
anonymous_user_path, db_session
)
@@ -116,7 +111,6 @@ async def login_as_anonymous_user(
token = generate_anonymous_user_jwt_token(tenant_id)
response = Response()
response.delete_cookie(FASTAPI_USERS_AUTH_COOKIE_NAME)
response.set_cookie(
key=ANONYMOUS_USER_COOKIE_NAME,
value=token,
@@ -130,48 +124,52 @@ async def login_as_anonymous_user(
@router.post("/product-gating")
def gate_product(
product_gating_request: ProductGatingRequest, _: None = Depends(control_plane_dep)
) -> ProductGatingResponse:
) -> None:
"""
Gating the product means that the product is not available to the tenant.
They will be directed to the billing page.
We gate the product when their subscription has ended.
We gate the product when
1) User has ended free trial without adding payment method
2) User's card has declined
"""
try:
store_product_gating(
product_gating_request.tenant_id, product_gating_request.application_status
)
return ProductGatingResponse(updated=True, error=None)
tenant_id = product_gating_request.tenant_id
token = CURRENT_TENANT_ID_CONTEXTVAR.set(tenant_id)
except Exception as e:
logger.exception("Failed to gate product")
return ProductGatingResponse(updated=False, error=str(e))
settings = load_settings()
settings.product_gating = product_gating_request.product_gating
store_settings(settings)
if product_gating_request.notification:
with get_session_with_tenant(tenant_id) as db_session:
create_notification(None, product_gating_request.notification, db_session)
if token is not None:
CURRENT_TENANT_ID_CONTEXTVAR.reset(token)
@router.get("/billing-information")
@router.get("/billing-information", response_model=BillingInformation)
async def billing_information(
_: User = Depends(current_admin_user),
) -> BillingInformation | SubscriptionStatusResponse:
) -> BillingInformation:
logger.info("Fetching billing information")
tenant_id = get_current_tenant_id()
return fetch_billing_information(tenant_id)
return BillingInformation(
**fetch_billing_information(CURRENT_TENANT_ID_CONTEXTVAR.get())
)
@router.post("/create-customer-portal-session")
async def create_customer_portal_session(
_: User = Depends(current_admin_user),
) -> dict:
tenant_id = get_current_tenant_id()
async def create_customer_portal_session(_: User = Depends(current_admin_user)) -> dict:
try:
# Fetch tenant_id and current tenant's information
tenant_id = CURRENT_TENANT_ID_CONTEXTVAR.get()
stripe_info = fetch_tenant_stripe_information(tenant_id)
stripe_customer_id = stripe_info.get("stripe_customer_id")
if not stripe_customer_id:
raise HTTPException(status_code=400, detail="Stripe customer ID not found")
logger.info(stripe_customer_id)
portal_session = stripe.billing_portal.Session.create(
customer=stripe_customer_id,
return_url=f"{WEB_DOMAIN}/admin/billing",
return_url=f"{WEB_DOMAIN}/admin/cloud-settings",
)
logger.info(portal_session)
return {"url": portal_session.url}
@@ -180,22 +178,6 @@ async def create_customer_portal_session(
raise HTTPException(status_code=500, detail=str(e))
@router.post("/create-subscription-session")
async def create_subscription_session(
_: User = Depends(current_admin_user),
) -> SubscriptionSessionResponse:
try:
tenant_id = CURRENT_TENANT_ID_CONTEXTVAR.get()
if not tenant_id:
raise HTTPException(status_code=400, detail="Tenant ID not found")
session_id = fetch_stripe_checkout_session(tenant_id)
return SubscriptionSessionResponse(sessionId=session_id)
except Exception as e:
logger.exception("Failed to create resubscription session")
raise HTTPException(status_code=500, detail=str(e))
@router.post("/impersonate")
async def impersonate_user(
impersonate_request: ImpersonateRequest,
@@ -204,7 +186,7 @@ async def impersonate_user(
"""Allows a cloud superuser to impersonate another user by generating an impersonation JWT token"""
tenant_id = get_tenant_id_for_email(impersonate_request.email)
with get_session_with_tenant(tenant_id=tenant_id) as tenant_session:
with get_session_with_tenant(tenant_id) as tenant_session:
user_to_impersonate = get_user_by_email(
impersonate_request.email, tenant_session
)
@@ -228,9 +210,8 @@ async def leave_organization(
user_email: UserByEmail,
current_user: User | None = Depends(current_admin_user),
db_session: Session = Depends(get_session),
tenant_id: str = Depends(get_current_tenant_id),
) -> None:
tenant_id = get_current_tenant_id()
if current_user is None or current_user.email != user_email.user_email:
raise HTTPException(
status_code=403, detail="You can only leave the organization as yourself"

View File

@@ -6,8 +6,6 @@ import stripe
from ee.onyx.configs.app_configs import STRIPE_PRICE_ID
from ee.onyx.configs.app_configs import STRIPE_SECRET_KEY
from ee.onyx.server.tenants.access import generate_data_plane_token
from ee.onyx.server.tenants.models import BillingInformation
from ee.onyx.server.tenants.models import SubscriptionStatusResponse
from onyx.configs.app_configs import CONTROL_PLANE_API_BASE_URL
from onyx.utils.logger import setup_logger
@@ -16,19 +14,6 @@ stripe.api_key = STRIPE_SECRET_KEY
logger = setup_logger()
def fetch_stripe_checkout_session(tenant_id: str) -> str:
token = generate_data_plane_token()
headers = {
"Authorization": f"Bearer {token}",
"Content-Type": "application/json",
}
url = f"{CONTROL_PLANE_API_BASE_URL}/create-checkout-session"
params = {"tenant_id": tenant_id}
response = requests.post(url, headers=headers, params=params)
response.raise_for_status()
return response.json()["sessionId"]
def fetch_tenant_stripe_information(tenant_id: str) -> dict:
token = generate_data_plane_token()
headers = {
@@ -42,9 +27,7 @@ def fetch_tenant_stripe_information(tenant_id: str) -> dict:
return response.json()
def fetch_billing_information(
tenant_id: str,
) -> BillingInformation | SubscriptionStatusResponse:
def fetch_billing_information(tenant_id: str) -> dict:
logger.info("Fetching billing information")
token = generate_data_plane_token()
headers = {
@@ -55,19 +38,8 @@ def fetch_billing_information(
params = {"tenant_id": tenant_id}
response = requests.get(url, headers=headers, params=params)
response.raise_for_status()
response_data = response.json()
# Check if the response indicates no subscription
if (
isinstance(response_data, dict)
and "subscribed" in response_data
and not response_data["subscribed"]
):
return SubscriptionStatusResponse(**response_data)
# Otherwise, parse as BillingInformation
return BillingInformation(**response_data)
billing_info = response.json()
return billing_info
def register_tenant_users(tenant_id: str, number_of_users: int) -> stripe.Subscription:

View File

@@ -1,8 +1,7 @@
from datetime import datetime
from pydantic import BaseModel
from onyx.server.settings.models import ApplicationStatus
from onyx.configs.constants import NotificationType
from onyx.server.settings.models import GatingType
class CheckoutSessionCreationRequest(BaseModel):
@@ -16,24 +15,15 @@ class CreateTenantRequest(BaseModel):
class ProductGatingRequest(BaseModel):
tenant_id: str
application_status: ApplicationStatus
class SubscriptionStatusResponse(BaseModel):
subscribed: bool
product_gating: GatingType
notification: NotificationType | None = None
class BillingInformation(BaseModel):
stripe_subscription_id: str
status: str
current_period_start: datetime
current_period_end: datetime
number_of_seats: int
cancel_at_period_end: bool
canceled_at: datetime | None
trial_start: datetime | None
trial_end: datetime | None
seats: int
subscription_status: str
billing_start: str
billing_end: str
payment_method_enabled: bool
@@ -58,12 +48,3 @@ class TenantDeletionPayload(BaseModel):
class AnonymousUserPath(BaseModel):
anonymous_user_path: str | None
class ProductGatingResponse(BaseModel):
updated: bool
error: str | None
class SubscriptionSessionResponse(BaseModel):
sessionId: str

View File

@@ -1,51 +0,0 @@
from typing import cast
from ee.onyx.configs.app_configs import GATED_TENANTS_KEY
from onyx.configs.constants import ONYX_CLOUD_TENANT_ID
from onyx.redis.redis_pool import get_redis_client
from onyx.redis.redis_pool import get_redis_replica_client
from onyx.server.settings.models import ApplicationStatus
from onyx.server.settings.store import load_settings
from onyx.server.settings.store import store_settings
from onyx.setup import setup_logger
from shared_configs.contextvars import CURRENT_TENANT_ID_CONTEXTVAR
logger = setup_logger()
def update_tenant_gating(tenant_id: str, status: ApplicationStatus) -> None:
redis_client = get_redis_client(tenant_id=ONYX_CLOUD_TENANT_ID)
# Store the full status
status_key = f"tenant:{tenant_id}:status"
redis_client.set(status_key, status.value)
# Maintain the GATED_ACCESS set
if status == ApplicationStatus.GATED_ACCESS:
redis_client.sadd(GATED_TENANTS_KEY, tenant_id)
else:
redis_client.srem(GATED_TENANTS_KEY, tenant_id)
def store_product_gating(tenant_id: str, application_status: ApplicationStatus) -> None:
try:
token = CURRENT_TENANT_ID_CONTEXTVAR.set(tenant_id)
settings = load_settings()
settings.application_status = application_status
store_settings(settings)
# Store gated tenant information in Redis
update_tenant_gating(tenant_id, application_status)
if token is not None:
CURRENT_TENANT_ID_CONTEXTVAR.reset(token)
except Exception:
logger.exception("Failed to gate product")
raise
def get_gated_tenants() -> set[str]:
redis_client = get_redis_replica_client(tenant_id=ONYX_CLOUD_TENANT_ID)
return cast(set[str], redis_client.smembers(GATED_TENANTS_KEY))

View File

@@ -24,7 +24,6 @@ from ee.onyx.server.tenants.user_mapping import get_tenant_id_for_email
from ee.onyx.server.tenants.user_mapping import user_owns_a_tenant
from onyx.auth.users import exceptions
from onyx.configs.app_configs import CONTROL_PLANE_API_BASE_URL
from onyx.configs.app_configs import DEV_MODE
from onyx.configs.constants import MilestoneRecordType
from onyx.db.engine import get_session_with_tenant
from onyx.db.engine import get_sqlalchemy_engine
@@ -86,8 +85,7 @@ async def create_tenant(email: str, referral_source: str | None = None) -> str:
# Provision tenant on data plane
await provision_tenant(tenant_id, email)
# Notify control plane
if not DEV_MODE:
await notify_control_plane(tenant_id, email, referral_source)
await notify_control_plane(tenant_id, email, referral_source)
except Exception as e:
logger.error(f"Tenant provisioning failed: {e}")
await rollback_tenant_provisioning(tenant_id)
@@ -118,7 +116,7 @@ async def provision_tenant(tenant_id: str, email: str) -> None:
# Await the Alembic migrations
await asyncio.to_thread(run_alembic_migrations, tenant_id)
with get_session_with_tenant(tenant_id=tenant_id) as db_session:
with get_session_with_tenant(tenant_id) as db_session:
configure_default_api_keys(db_session)
current_search_settings = (
@@ -134,7 +132,7 @@ async def provision_tenant(tenant_id: str, email: str) -> None:
add_users_to_tenant([email], tenant_id)
with get_session_with_tenant(tenant_id=tenant_id) as db_session:
with get_session_with_tenant(tenant_id) as db_session:
create_milestone_and_report(
user=None,
distinct_id=tenant_id,
@@ -200,35 +198,14 @@ async def rollback_tenant_provisioning(tenant_id: str) -> None:
def configure_default_api_keys(db_session: Session) -> None:
if ANTHROPIC_DEFAULT_API_KEY:
anthropic_provider = LLMProviderUpsertRequest(
name="Anthropic",
provider=ANTHROPIC_PROVIDER_NAME,
api_key=ANTHROPIC_DEFAULT_API_KEY,
default_model_name="claude-3-7-sonnet-20250219",
fast_default_model_name="claude-3-5-sonnet-20241022",
model_names=ANTHROPIC_MODEL_NAMES,
display_model_names=["claude-3-5-sonnet-20241022"],
)
try:
full_provider = upsert_llm_provider(anthropic_provider, db_session)
update_default_provider(full_provider.id, db_session)
except Exception as e:
logger.error(f"Failed to configure Anthropic provider: {e}")
else:
logger.error(
"ANTHROPIC_DEFAULT_API_KEY not set, skipping Anthropic provider configuration"
)
if OPENAI_DEFAULT_API_KEY:
open_provider = LLMProviderUpsertRequest(
name="OpenAI",
provider=OPENAI_PROVIDER_NAME,
api_key=OPENAI_DEFAULT_API_KEY,
default_model_name="gpt-4o",
default_model_name="gpt-4",
fast_default_model_name="gpt-4o-mini",
model_names=OPEN_AI_MODEL_NAMES,
display_model_names=["o1", "o3-mini", "gpt-4o", "gpt-4o-mini"],
)
try:
full_provider = upsert_llm_provider(open_provider, db_session)
@@ -240,6 +217,25 @@ def configure_default_api_keys(db_session: Session) -> None:
"OPENAI_DEFAULT_API_KEY not set, skipping OpenAI provider configuration"
)
if ANTHROPIC_DEFAULT_API_KEY:
anthropic_provider = LLMProviderUpsertRequest(
name="Anthropic",
provider=ANTHROPIC_PROVIDER_NAME,
api_key=ANTHROPIC_DEFAULT_API_KEY,
default_model_name="claude-3-5-sonnet-20241022",
fast_default_model_name="claude-3-5-sonnet-20241022",
model_names=ANTHROPIC_MODEL_NAMES,
)
try:
full_provider = upsert_llm_provider(anthropic_provider, db_session)
update_default_provider(full_provider.id, db_session)
except Exception as e:
logger.error(f"Failed to configure Anthropic provider: {e}")
else:
logger.error(
"ANTHROPIC_DEFAULT_API_KEY not set, skipping Anthropic provider configuration"
)
if COHERE_DEFAULT_API_KEY:
cloud_embedding_provider = CloudEmbeddingProviderCreationRequest(
provider_type=EmbeddingProvider.COHERE,

View File

@@ -28,7 +28,7 @@ def get_tenant_id_for_email(email: str) -> str:
def user_owns_a_tenant(email: str) -> bool:
with get_session_with_tenant(tenant_id=POSTGRES_DEFAULT_SCHEMA) as db_session:
with get_session_with_tenant(POSTGRES_DEFAULT_SCHEMA) as db_session:
result = (
db_session.query(UserTenantMapping)
.filter(UserTenantMapping.email == email)
@@ -38,7 +38,7 @@ def user_owns_a_tenant(email: str) -> bool:
def add_users_to_tenant(emails: list[str], tenant_id: str) -> None:
with get_session_with_tenant(tenant_id=POSTGRES_DEFAULT_SCHEMA) as db_session:
with get_session_with_tenant(POSTGRES_DEFAULT_SCHEMA) as db_session:
try:
for email in emails:
db_session.add(UserTenantMapping(email=email, tenant_id=tenant_id))
@@ -48,7 +48,7 @@ def add_users_to_tenant(emails: list[str], tenant_id: str) -> None:
def remove_users_from_tenant(emails: list[str], tenant_id: str) -> None:
with get_session_with_tenant(tenant_id=POSTGRES_DEFAULT_SCHEMA) as db_session:
with get_session_with_tenant(POSTGRES_DEFAULT_SCHEMA) as db_session:
try:
mappings_to_delete = (
db_session.query(UserTenantMapping)
@@ -71,7 +71,7 @@ def remove_users_from_tenant(emails: list[str], tenant_id: str) -> None:
def remove_all_users_from_tenant(tenant_id: str) -> None:
with get_session_with_tenant(tenant_id=POSTGRES_DEFAULT_SCHEMA) as db_session:
with get_session_with_tenant(POSTGRES_DEFAULT_SCHEMA) as db_session:
db_session.query(UserTenantMapping).filter(
UserTenantMapping.tenant_id == tenant_id
).delete()

View File

@@ -5,7 +5,7 @@ from fastapi import Depends
from sqlalchemy.orm import Session
from ee.onyx.db.token_limit import fetch_all_user_group_token_rate_limits_by_group
from ee.onyx.db.token_limit import fetch_user_group_token_rate_limits_for_user
from ee.onyx.db.token_limit import fetch_user_group_token_rate_limits
from ee.onyx.db.token_limit import insert_user_group_token_rate_limit
from onyx.auth.users import current_admin_user
from onyx.auth.users import current_curator_or_admin_user
@@ -51,10 +51,8 @@ def get_group_token_limit_settings(
) -> list[TokenRateLimitDisplay]:
return [
TokenRateLimitDisplay.from_db(token_rate_limit)
for token_rate_limit in fetch_user_group_token_rate_limits_for_user(
db_session=db_session,
group_id=group_id,
user=user,
for token_rate_limit in fetch_user_group_token_rate_limits(
db_session, group_id, user
)
]

View File

@@ -58,7 +58,6 @@ class UserGroup(BaseModel):
credential=CredentialSnapshot.from_credential_db_model(
cc_pair_relationship.cc_pair.credential
),
access_type=cc_pair_relationship.cc_pair.access_type,
)
for cc_pair_relationship in user_group_model.cc_pair_relationships
if cc_pair_relationship.is_current

View File

@@ -28,9 +28,3 @@ class EmbeddingModelTextType:
@staticmethod
def get_type(provider: EmbeddingProvider, text_type: EmbedTextType) -> str:
return EmbeddingModelTextType.PROVIDER_TEXT_TYPE_MAP[provider][text_type]
class GPUStatus:
CUDA = "cuda"
MAC_MPS = "mps"
NONE = "none"

View File

@@ -12,7 +12,6 @@ import voyageai # type: ignore
from cohere import AsyncClient as CohereAsyncClient
from fastapi import APIRouter
from fastapi import HTTPException
from fastapi import Request
from google.oauth2 import service_account # type: ignore
from litellm import aembedding
from litellm.exceptions import RateLimitError
@@ -98,17 +97,12 @@ class CloudEmbedding:
return final_embeddings
except Exception as e:
error_string = (
f"Exception embedding text with OpenAI - {type(e)}: "
f"Model: {model} "
f"Provider: {self.provider} "
f"Exception: {e}"
f"Error embedding text with OpenAI: {str(e)} \n"
f"Model: {model} \n"
f"Provider: {self.provider} \n"
f"Texts: {texts}"
)
logger.error(error_string)
# only log text when it's not an authentication error.
if not isinstance(e, openai.AuthenticationError):
logger.debug(f"Exception texts: {texts}")
raise RuntimeError(error_string)
async def _embed_cohere(
@@ -326,7 +320,6 @@ async def embed_text(
prefix: str | None,
api_url: str | None,
api_version: str | None,
gpu_type: str = "UNKNOWN",
) -> list[Embedding]:
if not all(texts):
logger.error("Empty strings provided for embedding")
@@ -380,11 +373,8 @@ async def embed_text(
elapsed = time.monotonic() - start
logger.info(
f"event=embedding_provider "
f"texts={len(texts)} "
f"chars={total_chars} "
f"provider={provider_type} "
f"elapsed={elapsed:.2f}"
f"Successfully embedded {len(texts)} texts with {total_chars} total characters "
f"with provider {provider_type} in {elapsed:.2f}"
)
elif model_name is not None:
logger.info(
@@ -413,14 +403,6 @@ async def embed_text(
f"Successfully embedded {len(texts)} texts with {total_chars} total characters "
f"with local model {model_name} in {elapsed:.2f}"
)
logger.info(
f"event=embedding_model "
f"texts={len(texts)} "
f"chars={total_chars} "
f"model={model_name} "
f"gpu={gpu_type} "
f"elapsed={elapsed:.2f}"
)
else:
logger.error("Neither model name nor provider specified for embedding")
raise ValueError(
@@ -473,15 +455,8 @@ async def litellm_rerank(
@router.post("/bi-encoder-embed")
async def route_bi_encoder_embed(
request: Request,
embed_request: EmbedRequest,
) -> EmbedResponse:
return await process_embed_request(embed_request, request.app.state.gpu_type)
async def process_embed_request(
embed_request: EmbedRequest, gpu_type: str = "UNKNOWN"
embed_request: EmbedRequest,
) -> EmbedResponse:
if not embed_request.texts:
raise HTTPException(status_code=400, detail="No texts to be embedded")
@@ -509,7 +484,6 @@ async def process_embed_request(
api_url=embed_request.api_url,
api_version=embed_request.api_version,
prefix=prefix,
gpu_type=gpu_type,
)
return EmbedResponse(embeddings=embeddings)
except RateLimitError as e:

View File

@@ -16,7 +16,6 @@ from model_server.custom_models import router as custom_models_router
from model_server.custom_models import warm_up_intent_model
from model_server.encoders import router as encoders_router
from model_server.management_endpoints import router as management_router
from model_server.utils import get_gpu_type
from onyx import __version__
from onyx.utils.logger import setup_logger
from shared_configs.configs import INDEXING_ONLY
@@ -59,10 +58,12 @@ def _move_files_recursively(source: Path, dest: Path, overwrite: bool = False) -
@asynccontextmanager
async def lifespan(app: FastAPI) -> AsyncGenerator:
gpu_type = get_gpu_type()
logger.notice(f"Torch GPU Detection: gpu_type={gpu_type}")
app.state.gpu_type = gpu_type
if torch.cuda.is_available():
logger.notice("CUDA GPU is available")
elif torch.backends.mps.is_available():
logger.notice("Mac MPS is available")
else:
logger.notice("GPU is not available, using CPU")
if TEMP_HF_CACHE_PATH.is_dir():
logger.notice("Moving contents of temp_huggingface to huggingface cache.")

View File

@@ -1,9 +1,7 @@
import torch
from fastapi import APIRouter
from fastapi import Response
from model_server.constants import GPUStatus
from model_server.utils import get_gpu_type
router = APIRouter(prefix="/api")
@@ -13,7 +11,10 @@ async def healthcheck() -> Response:
@router.get("/gpu-status")
async def route_gpu_status() -> dict[str, bool | str]:
gpu_type = get_gpu_type()
gpu_available = gpu_type != GPUStatus.NONE
return {"gpu_available": gpu_available, "type": gpu_type}
async def gpu_status() -> dict[str, bool | str]:
if torch.cuda.is_available():
return {"gpu_available": True, "type": "cuda"}
elif torch.backends.mps.is_available():
return {"gpu_available": True, "type": "mps"}
else:
return {"gpu_available": False, "type": "none"}

View File

@@ -8,9 +8,6 @@ from typing import Any
from typing import cast
from typing import TypeVar
import torch
from model_server.constants import GPUStatus
from onyx.utils.logger import setup_logger
logger = setup_logger()
@@ -61,12 +58,3 @@ def simple_log_function_time(
return cast(F, wrapped_sync_func)
return decorator
def get_gpu_type() -> str:
if torch.cuda.is_available():
return GPUStatus.CUDA
if torch.backends.mps.is_available():
return GPUStatus.MAC_MPS
return GPUStatus.NONE

View File

@@ -19,9 +19,6 @@ def prefix_external_group(ext_group_name: str) -> str:
return f"external_group:{ext_group_name}"
def build_ext_group_name_for_onyx(ext_group_name: str, source: DocumentSource) -> str:
"""
External groups may collide across sources, every source needs its own prefix.
NOTE: the name is lowercased to handle case sensitivity for group names
"""
return f"{source.value}_{ext_group_name}".lower()
def prefix_group_w_source(ext_group_name: str, source: DocumentSource) -> str:
"""External groups may collide across sources, every source needs its own prefix."""
return f"{source.value.upper()}_{ext_group_name}"

Some files were not shown because too many files have changed in this diff Show More